A general framework for finite mixtures of regression models using the EM algorithm is implemented. The E-step and all data handling are provided, while the M-step can be supplied by the user to easily define new models. Existing drivers implement mixtures of standard linear models, generalized linear models and model-based clustering.

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10.26 score 5 stars 103 dependents 878 scripts 33k downloads

network - Classes for Relational Data

Tools to create and modify network objects. The network class can represent a range of relational data types, and supports arbitrary vertex/edge/graph attributes.

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10.24 score 3 stars 154 dependents 3.5k scripts 36k downloads

agricolae - Statistical Procedures for Agricultural Research

Original idea was presented in the thesis "A statistical analysis tool for agricultural research" to obtain the degree of Master on science, National Engineering University (UNI), Lima-Peru. Some experimental data for the examples come from the CIP and others research. Agricolae offers extensive functionality on experimental design especially for agricultural and plant breeding experiments, which can also be useful for other purposes. It supports planning of lattice, Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin Squares, augmented block, factorial, split and strip plot designs. There are also various analysis facilities for experimental data, e.g. treatment comparison procedures and several non-parametric tests comparison, biodiversity indexes and consensus cluster.

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10.05 score 9 stars 18 dependents 4.5k scripts 52k downloads

RODBC - ODBC Database Access

An ODBC database interface.

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unixodbc

9.91 score 10 stars 32 dependents 4.4k scripts 19k downloads

'S4' classes and various tools for financial time series: Basic functions such as scaling and sorting, subsetting, mathematical operations and statistical functions.

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9.60 score 2 stars 134 dependents 1.4k scripts 36k downloads

interp - Interpolation Methods

Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide FOSS replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions. Linear interpolation is implemented in interp::interp(..., method="linear"), this corresponds to the call akima::interp(..., linear=TRUE) which is the default setting and covers most of akima::interp use cases in depending packages. A re-implementation of Akimas irregular grid spline interpolation (akima::interp(..., linear=FALSE)) is now also available via interp::interp(..., method="akima"). Estimators for partial derivatives are now also available in interp::locpoly(), these are a prerequisite for the spline interpolation. The basic part is a GPLed triangulation algorithm (sweep hull algorithm by David Sinclair) providing the starting point for the irregular grid interpolator. As side effect this algorithm is also used to provide replacements for almost all functions of the tripack package which also suffers from the same ACM license restrictions. All functions are designed to be backward compatible with their akima / tripack counterparts.

mcmc - Markov Chain Monte Carlo

Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012, <doi:10.1214/12-AOS1048>, function morph.metrop), which achieves geometric ergodicity by change of variable.

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9.05 score 144 dependents 390 scripts 17k downloads

compositions - Compositional Data Analysis

Provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations) in the way proposed by J. Aitchison and V. Pawlowsky-Glahn.

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openblas

8.97 score 1 stars 37 dependents 2.5k scripts 17k downloads

corpcor - Efficient Estimation of Covariance and (Partial) Correlation

Implements a James-Stein-type shrinkage estimator for the covariance matrix, with separate shrinkage for variances and correlations. The details of the method are explained in Schafer and Strimmer (2005) <DOI:10.2202/1544-6115.1175> and Opgen-Rhein and Strimmer (2007) <DOI:10.2202/1544-6115.1252>. The approach is both computationally as well as statistically very efficient, it is applicable to "small n, large p" data, and always returns a positive definite and well-conditioned covariance matrix. In addition to inferring the covariance matrix the package also provides shrinkage estimators for partial correlations and partial variances. The inverse of the covariance and correlation matrix can be efficiently computed, as well as any arbitrary power of the shrinkage correlation matrix. Furthermore, functions are available for fast singular value decomposition, for computing the pseudoinverse, and for checking the rank and positive definiteness of a matrix.

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8.82 score 333 dependents 1.3k scripts 53k downloads

bayesm - Bayesian Inference for Marketing/Micro-Econometrics

Covers many important models used in marketing and micro-econometrics applications. The package includes: Bayes Regression (univariate or multivariate dep var), Bayes Seemingly Unrelated Regression (SUR), Binary and Ordinal Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP), Multivariate Probit, Negative Binomial (Poisson) Regression, Multivariate Mixtures of Normals (including clustering), Dirichlet Process Prior Density Estimation with normal base, Hierarchical Linear Models with normal prior and covariates, Hierarchical Linear Models with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates, Hierarchical Negative Binomial Regression Models, Bayesian analysis of choice-based conjoint data, Bayesian treatment of linear instrumental variables models, Analysis of Multivariate Ordinal survey data with scale usage heterogeneity (as in Rossi et al, JASA (01)), Bayesian Analysis of Aggregate Random Coefficient Logit Models as in BLP (see Jiang, Manchanda, Rossi 2009) For further reference, consult our book, Bayesian Statistics and Marketing by Rossi, Allenby and McCulloch (Wiley second edition 2024) and Bayesian Non- and Semi-Parametric Methods and Applications (Princeton U Press 2014).

Estimation of a sparse inverse covariance matrix using a lasso (L1) penalty. Facilities are provided for estimates along a path of values for the regularization parameter.

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fortran

7.92 score 2 stars 113 dependents 572 scripts 21k downloads

registry - Infrastructure for R Package Registries

Provides a generic infrastructure for creating and using registries.

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7.75 score 183 dependents 189 scripts 54k downloads

A scoped options management framework. Used in other packages.

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7.55 score 1.2k dependents 16 scripts 118k downloads

trend - Non-Parametric Trend Tests and Change-Point Detection

The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.

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fortran

7.55 score 2 stars 12 dependents 1.3k scripts 5.3k downloads

speedglm - Fitting Linear and Generalized Linear Models to Large Data Sets

Fitting linear models and generalized linear models to large data sets by updating algorithms, according to the method described in Enea (2009, ISBN: 9788861294257).

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6.66 score 10 stars 13 dependents 412 scripts 14k downloads

ismev - An Introduction to Statistical Modeling of Extreme Values

Functions to support the computations carried out in `An Introduction to Statistical Modeling of Extreme Values' by Stuart Coles. The functions may be divided into the following groups; maxima/minima, order statistics, peaks over thresholds and point processes.

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6.63 score 1 stars 19 dependents 558 scripts 34k downloads

BGLR - Bayesian Generalized Linear Regression

Bayesian Generalized Linear Regression.

dslabs - Data Science Labs

Datasets and functions that can be used for data analysis practice, homework and projects in data science courses and workshops. 26 datasets are available for case studies in data visualization, statistical inference, modeling, linear regression, data wrangling and machine learning.

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6.22 score 2 dependents 4.7k scripts 5.8k downloads

frailtypack - Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints

The following several classes of frailty models using a penalized likelihood estimation on the hazard function but also a parametric estimation can be fit using this R package: 1) A shared frailty model (with gamma or log-normal frailty distribution) and Cox proportional hazard model. Clustered and recurrent survival times can be studied. 2) Additive frailty models for proportional hazard models with two correlated random effects (intercept random effect with random slope). 3) Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including two iid gamma random effects. 4) Joint frailty models in the context of the joint modelling for recurrent events with terminal event for clustered data or not. A joint frailty model for two semi-competing risks and clustered data is also proposed. 5) Joint general frailty models in the context of the joint modelling for recurrent events with terminal event data with two independent frailty terms. 6) Joint Nested frailty models in the context of the joint modelling for recurrent events with terminal event, for hierarchically clustered data (with two levels of clustering) by including two iid gamma random effects. 7) Multivariate joint frailty models for two types of recurrent events and a terminal event. 8) Joint models for longitudinal data and a terminal event. 9) Trivariate joint models for longitudinal data, recurrent events and a terminal event. 10) Joint frailty models for the validation of surrogate endpoints in multiple randomized clinical trials with failure-time and/or longitudinal endpoints with the possibility to use a mediation analysis model. 11) Conditional and Marginal two-part joint models for longitudinal semicontinuous data and a terminal event. 12) Joint frailty-copula models for the validation of surrogate endpoints in multiple randomized clinical trials with failure-time endpoints. 13) Generalized shared and joint frailty models for recurrent and terminal events. Proportional hazards (PH), additive hazard (AH), proportional odds (PO) and probit models are available in a fully parametric framework. For PH and AH models, it is possible to consider type-varying coefficients and flexible semiparametric hazard function. Prediction values are available (for a terminal event or for a new recurrent event). Left-truncated (not for Joint model), right-censored data, interval-censored data (only for Cox proportional hazard and shared frailty model) and strata are allowed. In each model, the random effects have the gamma or normal distribution. Now, you can also consider time-varying covariates effects in Cox, shared and joint frailty models (1-5). The package includes concordance measures for Cox proportional hazards models and for shared frailty models. 14) Competing Joint Frailty Model: A single type of recurrent event and two terminal events. 15) functions to compute power and sample size for four Gamma-frailty-based designs: Shared Frailty Models, Nested Frailty Models, Joint Frailty Models, and General Joint Frailty Models. Each design includes two primary functions: a power function, which computes power given a specified sample size; and a sample size function, which computes the required sample size to achieve a specified power. 16) Weibull Illness-Death model with or without shared frailty between transitions. Left-truncated and right-censored data are allowed. 17) Weibull Competing risks model with or without shared frailty between the transitions. Left-truncated and right-censored data are allowed. Moreover, the package can be used with its shiny application, in a local mode or by following the link below.

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fortranglibcopenmp

6.21 score 7 stars 2 dependents 114 scripts 1.7k downloads

Rank-based (R) estimation and inference for linear models. Estimation is for general scores and a library of commonly used score functions is included.

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5.95 score 11 dependents 125 scripts 4.4k downloads

VCA - Variance Component Analysis

ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.

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openblasfortran

5.95 score 2 stars 5 dependents 180 scripts 1.7k downloads

verification - Weather Forecast Verification

Utilities for verifying discrete, continuous and probabilistic forecasts, and forecasts expressed as parametric distributions are included.

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5.93 score 3 stars 9 dependents 617 scripts 1.7k downloads

pso - Particle Swarm Optimization

Provides an implementation of particle swarm optimisation consistent with the standard PSO 2007/2011 by Maurice Clerc. Additionally a number of ancillary routines are provided for easy testing and graphics.

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5.91 score 4 stars 34 dependents 158 scripts 6.3k downloads

SELF - A Structural Equation Embedded Likelihood Framework for Causal Discovery

Provides the SELF criteria to learn causal structure. Please cite "Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao. SELF: Structural Equational Embedded Likelihood Framework for Causal Discovery. AAAI. 2018."

rsatscan - Tools for Running the External 'SaTScan' Software using R Classes and Methods

The 'SaTScan'(TM) <https://www.satscan.org> software uses spatial and space-time scan statistics to detect and evaluate spatial and space-time clusters. With the 'rsatscan' package, you can run the external 'SaTScan' software from within R using R data formats. To successfully select appropriate parameter settings within 'rsatscan', you must first learn 'SaTScan'.

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5.66 score 10 stars 46 scripts 345 downloads

epiDisplay - Epidemiological Data Display Package

Package for data exploration and result presentation. Full 'epicalc' package with data management functions is available at '<https://medipe.psu.ac.th/epicalc/>'.

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5.65 score 2 stars 2 dependents 880 scripts 4.2k downloads

This is an substitute for the %V and %u formats which are not implemented on Windows. In addition, the package offers functions to convert from standard calender format yyyy-mm-dd to and from ISO 8601 week format yyyy-Www-d.

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5.43 score 2 stars 13 dependents 354 scripts 9.8k downloads

truncdist - Truncated Random Variables

A collection of tools to evaluate probability density functions, cumulative distribution functions, quantile functions and random numbers for truncated random variables. These functions are provided to also compute the expected value and variance. Nadarajah and Kotz (2006) developed most of the functions. QQ plots can be produced. All the probability functions in the stats, stats4 and evd packages are automatically available for truncation..

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5.42 score 23 dependents 510 scripts 7.5k downloads

relsurv - Relative Survival

Contains functions for analysing relative survival data, including nonparametric estimators of net (marginal relative) survival, relative survival ratio, crude mortality, methods for fitting and checking additive and multiplicative regression models, transformation approach, methods for dealing with population mortality tables. Work has been described in Pohar Perme, Pavlic (2018) <doi:10.18637/jss.v087.i08>.

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openblascpp

5.41 score 5 stars 5 dependents 69 scripts 5.0k downloads

tsModel - Time Series Modeling for Air Pollution and Health

Tools for specifying time series regression models.

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5.39 score 1 stars 9 dependents 233 scripts 6.6k downloads

compare - Comparing Objects for Differences

Functions to compare a model object to a comparison object. If the objects are not identical, the functions can be instructed to explore various modifications of the objects (e.g., sorting rows, dropping names) to see if the modified versions are identical.

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5.36 score 6 dependents 558 scripts 1.1k downloads

datarobot - 'DataRobot' Predictive Modeling API

For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.

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5.32 score 2 stars 350 scripts 293 downloads

som - Self-Organizing Map

Self-Organizing Map (with application in gene clustering).

openblas

4.58 score 4 stars 3 dependents 116 scripts 525 downloads

NlcOptim - Solve Nonlinear Optimization with Nonlinear Constraints

Optimization for nonlinear objective and constraint functions. Linear or nonlinear equality and inequality constraints are allowed. It accepts the input parameters as a constrained matrix.

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4.55 score 4 stars 13 dependents 39 scripts 5.8k downloads

fmri - Analysis of fMRI Experiments

Contains R-functions to perform an fMRI analysis as described in Polzehl and Tabelow (2019) <DOI:10.1007/978-3-030-29184-6>, Tabelow et al. (2006) <DOI:10.1016/j.neuroimage.2006.06.029>, Polzehl et al. (2010) <DOI:10.1016/j.neuroimage.2010.04.241>, Tabelow and Polzehl (2011) <DOI:10.18637/jss.v044.i11>.

Regression methods to quantify the relation between two measurement methods are provided by this package. In particular it addresses regression problems with errors in both variables and without repeated measurements. It implements the CLSI recommendations (see J. A. Budd et al. (2018, <https://clsi.org/standards/products/method-evaluation/documents/ep09/>) for analytical method comparison and bias estimation using patient samples. Furthermore, algorithms for Theil-Sen and equivariant Passing-Bablok estimators are implemented, see F. Dufey (2020, <doi:10.1515/ijb-2019-0157>) and J. Raymaekers and F. Dufey (2022, <arXiv:2202:08060>). A comprehensive overview over the implemented methods and references can be found in the manual pages "mcr-package" and "mcreg".

Bayesian regularization for feed-forward neural networks.

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openblasopenmp

4.34 score 5 dependents 116 scripts 4.2k downloads

BAwiR - Analysis of Basketball Data

Collection of tools to work with European basketball data. Functions available are related to friendly web scraping, data management and visualization. Data were obtained from <https://www.euroleaguebasketball.net/euroleague/>, <https://www.euroleaguebasketball.net/eurocup/> and <https://www.acb.com/>, following the instructions of their respectives robots.txt files, when available. Box score data are available for the three leagues. Play-by-play and spatial shooting data are also available for the Spanish league. Methods for analysis include a population pyramid, 2D plots, circular plots of players' percentiles, plots of players' monthly/yearly stats, team heatmaps, team shooting plots, team four factors plots, cross-tables with the results of regular season games, maps of nationalities, combinations of lineups, possessions-related variables, timeouts, performance by periods, personal fouls, offensive rebounds and different types of shooting charts. Please see Vinue (2020) <doi:10.1089/big.2018.0124> and Vinue (2024) <doi:10.1089/big.2023.0177>.

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4.31 score 2 stars 43 scripts 549 downloads

ars - Adaptive Rejection Sampling

Adaptive Rejection Sampling, Original version.

GPfit - Gaussian Processes Modeling

A computationally stable approach of fitting a Gaussian Process (GP) model to a deterministic simulator.

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4.16 score 1 stars 4 dependents 167 scripts 7.2k downloads

Rlab - Functions and Datasets Required for ST370 Class

Provides functions and datasets required for the ST 370 course at North Carolina State University.

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4.16 score 8 dependents 598 scripts 796 downloads

misty - Miscellaneous Functions 'T. Yanagida'

Miscellaneous functions for (1) data handling (e.g., grand-mean and group-mean centering, coding variables and reverse coding items, scale and cluster scores, reading and writing Excel and SPSS files), (2) descriptive statistics (e.g., frequency table, cross tabulation, effect size measures), (3) missing data (e.g., descriptive statistics for missing data, missing data pattern, Little's test of Missing Completely at Random, and auxiliary variable analysis), (4) multilevel data (e.g., multilevel descriptive statistics, within-group and between-group correlation matrix, multilevel confirmatory factor analysis, level-specific fit indices, cross-level measurement equivalence evaluation, multilevel composite reliability, and multilevel R-squared measures), (5) item analysis (e.g., confirmatory factor analysis, coefficient alpha and omega, between-group and longitudinal measurement equivalence evaluation), (6) statistical analysis (e.g., bootstrap confidence intervals, collinearity and residual diagnostics, dominance analysis, between- and within-subject analysis of variance, latent class analysis, t-test, z-test, sample size determination), and (7) functions to interact with 'Blimp' and 'Mplus'.

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4.15 score 1 stars 1 dependents 199 scripts 3.4k downloads

sda - Shrinkage Discriminant Analysis and CAT Score Variable Selection

Provides an efficient framework for high-dimensional linear and diagonal discriminant analysis with variable selection. The classifier is trained using James-Stein-type shrinkage estimators and predictor variables are ranked using correlation-adjusted t-scores (CAT scores). Variable selection error is controlled using false non-discovery rates or higher criticism.

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4.15 score 2 dependents 65 scripts 3.6k downloads

Mercator - Clustering and Visualizing Distance Matrices

Defines the classes used to explore, cluster and visualize distance matrices, especially those arising from binary data. See Abrams and colleagues, 2021, <doi:10.1093/bioinformatics/btab037>.

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clustering

4.13 score 1 dependents 15 scripts 677 downloads

Is designed to interactively and reproducibly visualize and filter SNP (single-nucleotide polymorphism) datasets. This R-based implementation of SNP and genotype filters facilitates an interactive and iterative SNP filtering pipeline, which can be documented reproducibly via 'rmarkdown'. 'SNPfiltR' contains functions for visualizing various quality and missing data metrics for a SNP dataset, and then filtering the dataset based on user specified cutoffs. All functions take 'vcfR' objects as input, which can easily be generated by reading standard vcf (variant call format) files into R using the R package 'vcfR' authored by Knaus and Grünwald (2017) <doi:10.1111/1755-0998.12549>. Each 'SNPfiltR' function can return a newly filtered 'vcfR' object, which can then be written to a local directory in standard vcf format using the 'vcfR' package, for downstream population genetic and phylogenetic analyses.

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4.00 score 198 scripts 638 downloads

hpfilter - The One- And Two-Sided Hodrick-Prescott Filter

Provides two functions that implement the one-sided and two-sided versions of the Hodrick-Prescott filter. The one-sided version is a Kalman filter-based implementation, whereas the two- sided version uses sparse matrices for improved efficiency. References: Hodrick, R. J., and Prescott, E. C. (1997) <doi:10.2307/2953682> Mcelroy, T. (2008) <doi:10.1111/j.1368-423X.2008.00230.x> Meyer-Gohde, A. (2010) <https://ideas.repec.org/c/dge/qmrbcd/181.html> For more references, see the vignette.

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4.00 score 2 stars 1 dependents 33 scripts 481 downloads

mixdist - Finite Mixture Distribution Models

Fit finite mixture distribution models to grouped data and conditional data by maximum likelihood using a combination of a Newton-type algorithm and the EM algorithm.

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3.99 score 3 dependents 109 scripts 446 downloads

spacc - Fast Spatial Species Accumulation Curves

High-performance spatial species accumulation curves using nearest-neighbor algorithms. Implements 'kNN' and 'kNCN' sampling methods with a 'C++' backend for speed. Supports Hill numbers (q=0,1,2), beta diversity partitioning (turnover/nestedness), coverage-based rarefaction and extrapolation, phylogenetic diversity (Faith's PD, mean pairwise distance, mean nearest taxon distance), functional diversity accumulation, diversity-area relationships (DAR), endemism-area curves, sampling-effort correction and fragmentation analysis, and species-area relationship (SAR) models based on extreme value theory (EVT). Multiple starting points (seeds) provide uncertainty quantification. Methods are described in 'Chao' et al. (2014) <doi:10.1890/13-0133.1>, 'Baselga' (2010) <doi:10.1111/j.1466-8238.2009.00490.x>, 'Chao' and 'Jost' (2012) <doi:10.1890/11-1952.1>, 'Faith' (1992) <doi:10.1016/0006-3207(92)91201-3>, 'Ma' (2018) <doi:10.1002/ece3.4526>, 'Borda-de-Agua' et al. (2025) <doi:10.1038/s41467-025-59239-7>, 'Hanski' et al. (2013) <doi:10.1073/pnas.1311190110>, and 'Jost' (2007) <doi:10.1890/06-1736.1>.

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cpp

3.99 score 28 scripts

binhf - Haar-Fisz Functions for Binomial Data

Binomial Haar-Fisz transforms for Gaussianization as in Nunes and Nason (2009).

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3.99 score 3 dependents 258 scripts 4.2k downloads

changepoint.np - Methods for Nonparametric Changepoint Detection

Implements the multiple changepoint algorithm PELT with a nonparametric cost function based on the empirical distribution of the data. This package extends the changepoint package (see Killick, R and Eckley, I (2014) <doi:10.18637/jss.v058.i03> ).

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3.98 score 2 stars 3 dependents 53 scripts 490 downloads

geigen - Calculate Generalized Eigenvalues, the Generalized Schur Decomposition and the Generalized Singular Value Decomposition of a Matrix Pair with Lapack

Functions to compute generalized eigenvalues and eigenvectors, the generalized Schur decomposition and the generalized Singular Value Decomposition of a matrix pair, using Lapack routines.

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openblas

3.98 score 1 stars 22 dependents 121 scripts 1.2k downloads

FARS - Factor-Augmented Regression Scenarios

Provides a comprehensive framework in R for modeling and forecasting economic scenarios based on multi-level dynamic factor model. The package enables users to: (i) extract global and group-specific factors using a flexible multi-level factor structure; (ii) compute asymptotically valid confidence regions for the estimated factors, accounting for uncertainty in the factor loadings; (iii) obtain estimates of the parameters of the factor-augmented quantile regressions together with their standard deviations; (iv) recover full predictive conditional densities from estimated quantiles; (v) obtain risk measures based on extreme quantiles of the conditional densities; (vi) estimate the conditional density and the corresponding extreme quantiles when the factors are stressed.

A set of functions to perform distribution-free Bayesian analyses. Included are Bayesian analogues to the frequentist Mann-Whitney U test, the Wilcoxon Signed-Ranks test, Kendall's Tau Rank Correlation Coefficient, Goodman and Kruskal's Gamma, McNemar's Test, the binomial test, the sign test, the median test, as well as distribution-free methods for testing contrasts among condition and for computing Bayes factors for hypotheses. The package also includes procedures to estimate the power of distribution-free Bayesian tests based on data simulations using various probability models for the data. The set of functions provide data analysts with a set of Bayesian procedures that avoids requiring parametric assumptions about measurement error and is robust to problem of extreme outlier scores.

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3.92 score 2 dependents 3 scripts 617 downloads

CB2 - CRISPR Pooled Screen Analysis using Beta-Binomial Test

Provides functions for hit gene identification and quantification of sgRNA (single-guided RNA) abundances for CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) pooled screen data analysis. Details are in Jeong et al. (2019) <doi:10.1101/gr.245571.118> and Baggerly et al. (2003) <doi:10.1093/bioinformatics/btg173>.

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cpp

3.92 score 42 scripts 280 downloads

GB2 - Generalized Beta Distribution of the Second Kind: Properties, Likelihood, Estimation

The GB2 package explores the Generalized Beta distribution of the second kind. Density, cumulative distribution function, quantiles and moments of the distribution are given. Functions for the full log-likelihood, the profile log-likelihood and the scores are provided. Formulas for various indicators of inequality and poverty under the GB2 are implemented. The GB2 is fitted by the methods of maximum pseudo-likelihood estimation using the full and profile log-likelihood, and non-linear least squares estimation of the model parameters. Various plots for the visualization and analysis of the results are provided. Variance estimation of the parameters is provided for the method of maximum pseudo-likelihood estimation. A mixture distribution based on the compounding property of the GB2 is presented (denoted as "compound" in the documentation). This mixture distribution is based on the discretization of the distribution of the underlying random scale parameter. The discretization can be left or right tail. Density, cumulative distribution function, moments and quantiles for the mixture distribution are provided. The compound mixture distribution is fitted using the method of maximum pseudo-likelihood estimation. The fit can also incorporate the use of auxiliary information. In this new version of the package, the mixture case is complemented with new functions for variance estimation by linearization and comparative density plots.

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3.92 score 1 stars 3 dependents 97 scripts 3.2k downloads

adlift - An Adaptive Lifting Scheme Algorithm

Adaptive wavelet lifting transforms for signal denoising using optimal local neighbourhood regression, from Nunes et al. (2006) <doi:10.1007/s11222-006-6560-y>.

GHRexplore - Exploratory Analysis of Temporal and Spatio-Temporal Health Data

A collection of commonly used visualizations of temporal and spatio-temporal health data including case counts, incidence rates, and covariates. The available plot types include time series, heatmaps, seasonality plots, maps and more. The package supports standard data transformations such as temporal and spatial aggregations, while offering extensive customization options for the resulting figures.

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3.88 score 1 stars 1 dependents 9 scripts 197 downloads

OpenLand - Quantitative Analysis and Visualization of LUCC

Tools for the analysis of land use and cover (LUC) time series. It includes support for loading spatiotemporal raster data and synthesized spatial plotting. Several LUC change (LUCC) metrics in regular or irregular time intervals can be extracted and visualized through one- and multistep sankey and chord diagrams. A complete intensity analysis according to Aldwaik and Pontius (2012) <doi:10.1016/j.landurbplan.2012.02.010> is implemented, including tools for the generation of standardized multilevel output graphics.

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3.87 score 3 stars 49 scripts 75 downloads

ibmdbR - IBM in-Database Analytics for R

Functionality required to efficiently use R with IBM(R) Db2(R) Warehouse offerings (formerly IBM dashDB(R)) and IBM Db2 for z/OS(R) in conjunction with IBM Db2 Analytics Accelerator for z/OS. Many basic and complex R operations are pushed down into the database, which removes the main memory boundary of R and allows to make full use of parallel processing in the underlying database. For executing R-functions in a multi-node environment in parallel the idaTApply() function requires the 'SparkR' package (<https://spark.apache.org/docs/latest/sparkr.html>). The optional 'ggplot2' package is needed for the plot.idaLm() function only.

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3.86 score 2 stars 72 scripts 303 downloads

hsphase - Phasing, Pedigree Reconstruction, Sire Imputation and Recombination Events Identification of Half-sib Families Using SNP Data

Identification of recombination events, haplotype reconstruction, sire imputation and pedigree reconstruction using half-sib family SNP data.

Fits a spatially discrete approximation to a log-Gaussian Cox process model for spatially aggregated disease count data, estimated by Monte Carlo Maximum Likelihood as in Christensen (2004) <doi:10.1198/106186004X2525> and Johnson, Diggle and Giorgi (2019) <doi:10.1002/sim.8339>. Performance-critical steps (aggregated correlation assembly, 'MALA' sampling, the Monte Carlo likelihood, and the Kronecker-structured space-time likelihood) are implemented in C++ via 'RcppArmadillo'. Provides a one-line, 'glm'-like interface and statistical extensions including a nugget term, general 'Matern' smoothness, raster and misaligned covariates, restricted spatial regression, importance-sampling diagnostics and re-anchored 'MCML'.

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openblascppopenmp

3.82 score 22 scripts

survIDINRI - IDI and NRI for Comparing Competing Risk Prediction Models with Censored Survival Data

Performs inference for a class of measures to compare competing risk prediction models with censored survival data. The class includes the integrated discrimination improvement index (IDI) and category-less net reclassification index (NRI).

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3.82 score 1 stars 1 dependents 42 scripts 1.0k downloads

erer - Empirical Research in Economics with R

Several functions, datasets, and sample codes related to empirical research in economics are included. They cover the marginal effects for binary or ordered choice models, static and dynamic Almost Ideal Demand System (AIDS) models, and a typical event analysis in finance.

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3.81 score 3 stars 1 dependents 223 scripts 3.2k downloads

LTASR - Functions to Replicate the Center for Disease Control and Prevention's 'LTAS' Software in R

A suite of functions for reading in a rate file in XML format, stratify a cohort, and calculate 'SMRs' from the stratified cohort and rate file.

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3.81 score 32 scripts 185 downloads

CytobankAPI - Cytobank API Wrapper for R

Tools to interface with Cytobank's API via R, organized by endpoints that represent various areas of Cytobank functionality. Learn more about Cytobank at <https://www.beckman.com/flow-cytometry/software>.

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3.79 score 61 scripts 840 downloads

easyNCDF - Tools to Easily Read/Write NetCDF Files into/from Multidimensional R Arrays

Set of wrappers for the 'ncdf4' package to simplify and extend its reading/writing capabilities into/from multidimensional R arrays.

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3.77 score 7 dependents 28 scripts 434 downloads

pmsampsize - Sample Size for Development of a Prediction Model

Computes the minimum sample size required for the development of a new multivariable prediction model using the criteria proposed by Riley et al. (2018) <doi: 10.1002/sim.7992>. pmsampsize can be used to calculate the minimum sample size for the development of models with continuous, binary or survival (time-to-event) outcomes. Riley et al. (2018) <doi: 10.1002/sim.7992> lay out a series of criteria the sample size should meet. These aim to minimise the overfitting and to ensure precise estimation of key parameters in the prediction model.

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3.76 score 5 stars 1 dependents 48 scripts 1.1k downloads

prepR4pcm - Prepare Data and Trees for Phylogenetic Comparative Methods

Reconcile species names across datasets and phylogenetic trees for comparative biology workflows. Identifies mismatches due to formatting differences, taxonomic synonymy, and spelling errors. Produces detailed reports documenting how each name was resolved, which taxonomic authority was used, and what remains unresolved. Supports exact matching, name normalisation, synonym resolution via local taxonomic databases, and fuzzy matching for likely typos. Detects taxonomic splits and lumps. For methodological context, see Nakagawa et al. (2026) <doi:10.32942/X2468Z>.

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3.76 score 19 scripts

HiddenMarkov - Hidden Markov Models

Contains functions for the analysis of Discrete Time Hidden Markov Models, Markov Modulated GLMs and the Markov Modulated Poisson Process. It includes functions for simulation, parameter estimation, and the Viterbi algorithm. See the topic "HiddenMarkov" for an introduction to the package, and "Change Log" for a list of recent changes. The algorithms are based of those of Walter Zucchini.

Visualization and analysis of spatially resolved transcriptomics data. The 'spatialGE' R package provides methods for visualizing and analyzing spatially resolved transcriptomics data, such as 10X Visium, CosMx, or csv/tsv gene expression matrices. It includes tools for spatial interpolation, autocorrelation analysis, tissue domain detection, gene set enrichment, and differential expression analysis using spatial mixed models.

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cpp

3.70 score 50 scripts 173 downloads

osdatahub - Easier Interaction with the Ordnance Survey Data Hub

Ordnance Survey ('OS') is the national mapping agency for Great Britain and produces a large variety of mapping and geospatial products. Much of OS's data is available via the OS Data Hub <https://osdatahub.os.uk/>, a platform that hosts both free and premium data products. 'osdatahub' provides a user-friendly way to access, query, and download these data.

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3.70 score 20 scripts 629 downloads

cyjShiny - Cytoscape.js Shiny Widget (cyjShiny)

Wraps cytoscape.js as a shiny widget. cytoscape.js <https://js.cytoscape.org/> is a Javascript-based graph theory (network) library for visualization and analysis. This package supports the visualization of networks with custom visual styles and several available layouts. Demo Shiny applications are provided in the package code.

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3.69 score 99 scripts 214 downloads

Ts - Calculation of the Surface Temperature (Ts) from Geospatial Raster Data

Provides functions to calculate the Surface Temperature (Ts) from geospatial raster data. These functions use albedo, Normalized Difference Vegetation Index (NDVI), and air temperature (Ta) to estimate Ts, facilitating hydrological, ecological, and remote sensing analyses.

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3.69 score 980 scripts 166 downloads

aurora - Build Stateless Web Apps with 'plumber2'

A scaffolding and deployment toolkit for building stateless web applications in R on top of the 'plumber2' web framework (<https://plumber2.posit.co/>). The UI is authored with 'bslib' and compiled to a static HTML asset at build time, while 'plumber2' serves the assets and exposes JSON API routes. Provides functions to scaffold app skeletons, run them locally, and generate Dockerfiles and images suitable for 'ShinyProxy' or plain Docker.

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3.68 score 19 scripts

REAT - Regional Economic Analysis Toolbox

Collection of models and analysis methods used in regional and urban economics and (quantitative) economic geography, e.g. measures of inequality, regional disparities and convergence, regional specialization as well as accessibility and spatial interaction models.

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3.68 score 3 stars 158 scripts 332 downloads

Rmosek - The R to MOSEK Optimization Interface

This is a meta-package designed to support the installation of Rmosek (>= 6.0) and bring the optimization facilities of MOSEK (>= 6.0) to the R-language. The interface supports large-scale optimization of many kinds: Mixed-integer and continuous linear, second-order cone, exponential cone and power cone optimization, as well as continuous semidefinite optimization. Rmosek and the R-language are open-source projects. MOSEK is a proprietary product, but unrestricted trial and academic licenses are available.

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3.67 score 2 stars 4 dependents 48 scripts 4.1k downloads

callback - Computes Statistics from Discrimination Experimental Data

In discrimination experiments candidates are sent on the same test (e.g. job, house rental) and one examines whether they receive the same outcome. The number of non negative answers are first examined in details looking for outcome differences. Then various statistics are computed. This package can also be used for analyzing the results from random experiments.

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3.67 score 235 scripts 150 downloads

aweSOM - Interactive Self-Organizing Maps

Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM on numeric, categorical or mixed data, as well as tools to evaluate the quality of SOM.

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3.67 score 3 stars 1 dependents 52 scripts 368 downloads

groupcompare - Comparing Two Groups Using Various Descriptive Statistics

Comparing two independent or paired groups across a range of descriptive statistics, enabling the evaluation of potential differences in central tendency (mean, median), dispersion (variance, interquartile range), shape (skewness, kurtosis), and distributional characteristics (various quantiles). The analytical framework incorporates parametric t-tests, non-parametric Wilcoxon tests, permutation tests, and bootstrap resampling techniques to assess the statistical significance of observed differences.

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3.65 score 1 dependents 5 scripts 155 downloads

gif - Graphical Independence Filtering

Provides a method of recovering the precision matrix for Gaussian graphical models efficiently. Our approach could be divided into three categories. First of all, we use Hard Graphical Thresholding for best subset selection problem of Gaussian graphical model, and the core concept of this method was proposed by Luo et al. (2014) <arXiv:1407.7819>. Secondly, a closed form solution for graphical lasso under acyclic graph structure is implemented in our package (Fattahi and Sojoudi (2019) <https://jmlr.org/papers/v20/17-501.html>). Furthermore, we implement block coordinate descent algorithm to efficiently solve the covariance selection problem (Dempster (1972) <doi:10.2307/2528966>). Our package is computationally efficient and can solve ultra-high-dimensional problems, e.g. p > 10,000, in a few minutes.

Implements the SoftBart model of described by Linero and Yang (2018) <doi:10.1111/rssb.12293>, with the optional use of a sparsity-inducing prior to allow for variable selection. For usability, the package maintains the same style as the 'BayesTree' package.

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openblascpp

3.56 score 1 dependents 122 scripts 785 downloads

SAPP - Statistical Analysis of Point Processes

Functions for statistical analysis of point processes.

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glibc

3.56 score 36 scripts 518 downloads

ringbp - Simulate and Evaluate Targeted Interventions in Infectious Disease Outbreaks

Branching process simulation model of infectious disease transmission with flexible parameterisation of epidemiology and targeted interventions, including isolation, contact tracing and quarantine, to reduce transmission, together with functions to evaluate outbreak control. Introduced in Hellewell et al. (2020) <doi:10.1016/S2214-109X(20)30074-7>.

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3.56 score 24 scripts

biganalytics - Utilities for 'big.matrix' Objects from Package 'bigmemory'

Extend the 'bigmemory' package with various analytics. Functions 'bigkmeans' and 'binit' may also be used with native R objects. For 'tapply'-like functions, the bigtabulate package may also be helpful. For linear algebra support, see 'bigalgebra'. For mutex (locking) support for advanced shared-memory usage, see 'synchronicity'.

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cpp

3.55 score 1 stars 5 dependents 238 scripts 947 downloads

kofn - Maximum Likelihood Estimation for k-Out-of-n System Data

Maximum likelihood estimation of component lifetime parameters from system-level observations of k-out-of-n systems. Supports exponential and Weibull component distributions under multiple observation schemes: Scheme 0 (system lifetime only), Scheme 1 (periodic inspection), and Scheme 2 (complete monitoring). Provides an EM algorithm for Weibull parallel systems and Fisher information comparison across schemes. The k-out-of-n framework unifies series (k=1) and parallel (k=m) systems as a censoring problem on component lifetimes. Conforms to the 'likelihood.model' generics and returns fitted objects compatible with 'algebraic.mle'. The data-generating process and topology infrastructure (system survival, density, signature, structure function, importance measures) are delegated to the 'dist.structure' package; 'kofn' focuses exclusively on inference for the k-out-of-n family.

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3.54 score 9 scripts

vectorsurvR - Data Access and Analytical Tools for 'VectorSurv' Users

Allows registered 'VectorSurv' <https://vectorsurv.org/> users access to data through the 'VectorSurv API' <https://api.vectorsurv.org/>. Additionally provides functions for analysis and visualization.

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3.54 score 9 scripts 612 downloads

interleave - Converts Tabular Data to Interleaved Vectors

Converts matrices and lists of matrices into a single vector by interleaving their values. That is, each element of the result vector is filled from the input matrices one row at a time. This is the same as transposing a matrix, then removing the dimension attribute, but is designed to operate on matrices in nested list structures.

A framework for fitting adaptive forecasting models. Provides a way to use forecasts as input to models, e.g. weather forecasts for energy related forecasting. The models can be fitted recursively and can easily be setup for updating parameters when new data arrives. See the included vignettes, the website <https://onlineforecasting.org> and the paper "onlineforecast: An R package for adaptive and recursive forecasting" <https://journal.r-project.org/articles/RJ-2023-031/>.

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openblascpp

3.48 score 3 stars 25 scripts 260 downloads

prevtoinc - Prevalence to Incidence Calculations for Point-Prevalence Studies in a Nosocomial Setting

Functions to simulate point prevalence studies (PPSs) of healthcare-associated infections (HAIs) and to convert prevalence to incidence in steady state setups. Companion package to the preprint Willrich et al., From prevalence to incidence - a new approach in the hospital setting; <doi:10.1101/554725> , where methods are explained in detail.

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3.48 score 1 dependents 20 scripts 148 downloads

RSentiment - Analyse Sentiment of English Sentences

Analyses sentiment of a sentence in English and assigns score to it. It can classify sentences to the following categories of sentiments:- Positive, Negative, very Positive, very negative, Neutral. For a vector of sentences, it counts the number of sentences in each category of sentiment.In calculating the score, negation and various degrees of adjectives are taken into consideration. It deals only with English sentences.

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openjdk

3.48 score 60 scripts 217 downloads

cdfquantreg - Quantile Regression for Random Variables on the Unit Interval

Employs a two-parameter family of distributions for modelling random variables on the (0, 1) interval by applying the cumulative distribution function (cdf) of one parent distribution to the quantile function of another.

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3.47 score 2 stars 37 scripts 356 downloads

zetadiv - Functions to Compute Compositional Turnover Using Zeta Diversity

Functions to compute compositional turnover using zeta-diversity, the number of species shared by multiple assemblages. The package includes functions to compute zeta-diversity for a specific number of assemblages and to compute zeta-diversity for a range of numbers of assemblages. It also includes functions to explain how zeta-diversity varies with distance and with differences in environmental variables between assemblages, using generalised linear models, linear models with negative constraints, generalised additive models,shape constrained additive models, and I-splines.

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3.46 score 3 stars 1 dependents 81 scripts 577 downloads

rmcfs - The MCFS-ID Algorithm for Feature Selection and Interdependency Discovery

MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, 'small n large p' transactional and biological data. M. Draminski, J. Koronacki (2018) <doi:10.18637/jss.v085.i12>.

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openjdk

3.46 score 1 stars 1 dependents 32 scripts 299 downloads

ConfusionTableR - Confusion Matrix Toolset

Takes the outputs of a 'caret' confusion matrix and allows for the quick conversion of these list items to lists. The intended usage is to allow the tool to work with the outputs of machine learning classification models. This tool works with classification problems for binary and multi-classification problems and allows for the record level conversion of the confusion matrix outputs. This is useful, as it allows quick conversion of these objects for storage in database systems and to track ML model performance over time. Traditionally, this approach has been used for highlighting model representation and feature slippage.

A multiple-testing procedure for high-dimensional mediation hypotheses. Mediation analysis is of rising interest in epidemiology and clinical trials. Among existing methods for mediation analyses, the popular joint significance (JS) test yields an overly conservative type I error rate and therefore low power. In the R package 'HDMT' we implement a multiple-testing procedure that accurately controls the family-wise error rate (FWER) and the false discovery rate (FDR) when using JS for testing high-dimensional mediation hypotheses. The core of our procedure is based on estimating the proportions of three component null hypotheses and deriving the corresponding mixture distribution of null p-values. Results of the data examples include better-behaved quantile-quantile plots and improved detection of novel mediation relationships on the role of DNA methylation in genetic regulation of gene expression. With increasing interest in mediation by molecular intermediaries such as gene expression, the proposed method addresses an unmet methodological challenge. Methods used in the package refer to James Y. Dai, Janet L. Stanford & Michael LeBlanc (2020) <doi:10.1080/01621459.2020.1765785>.

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3.40 score 3 dependents 28 scripts 441 downloads

transitiontrees - Transition Trajectories and Dynamics of Variable-Length Pathways or Sequences

Analyzes transition trajectories in event, sequence, and ordered data, focusing on how states follow one another, how far processes unfold, and where pathways branch or converge. Trajectories are modeled using variable-order prediction suffix trees (Ron, Singer, & Tishby, 1996) <doi:10.1023/A:1026490906255>, implemented in both frequency-based and prediction-based forms. The framework includes multiple pruning, validation, and smoothing techniques to ensure model robustness. Visualization options include transition trees, radial sunburst diagrams, transition heatmaps, and forward trajectory trees.

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3.40 score

sysreqr - Preflight Checks for 'R' Package System Requirements

Helps users on 'Linux' (and, where applicable, 'macOS') find the system packages they need before installing 'R' packages from source. Queries maintained system requirement sources, reports missing system packages, and generates installation commands, 'Dockerfile' snippets, 'GitHub Actions' steps, administrator request templates, and diagnostic reports from failed installation logs.

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3.40 score 5 scripts

seine - Semiparametric Ecological Inference

Efficient and user-friendly routines for modern ecological inference. Implements the methods described in McCartan & Kuriwaki (2025+) <doi:10.48550/arXiv.2509.20194>, which generalize ecological regression as introduced by Goodman (1953) <doi:10.2307/2088121>. Includes routines for preprocessing, synthetic data generation, double/debiased machine learning (DML) estimation, partial identification bounds, and sensitivity analysis.

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openblascppopenmp

3.40 score 9 scripts

ATNr - Run Allometric Trophic Networks Models

Implements the differential equations associated to different versions of Allometric Trophic Models (ATN) to estimate the temporal dynamics of species biomasses in food webs. It offers several features to generate synthetic food webs and to parametrise models as well as a wrapper to the ODE solver deSolve.

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openblascppopenmp

3.40 score 25 scripts 275 downloads

behaviorchange - Tools for Behavior Change Researchers and Professionals

Contains specialised analyses and visualisation tools for behavior change science. These facilitate conducting determinant studies (for example, using confidence interval-based estimation of relevance, CIBER, or CIBERlite plots, see Crutzen, Noijen & Peters (2017) <doi:10/ghtfz9>), systematically developing, reporting, and analysing interventions (for example, using Acyclic Behavior Change Diagrams), and reporting about intervention effectiveness (for example, using the Numbers Needed for Change, see Gruijters & Peters (2017) <doi:10/jzkt>), and computing the required sample size (using the Meaningful Change Definition, see Gruijters & Peters (2020) <doi:10/ghpnx8>). This package is especially useful for researchers in the field of behavior change or health psychology and to behavior change professionals such as intervention developers and prevention workers.

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3.40 score 10 scripts 506 downloads

RWsearch - Lazy Search in R Packages, Task Views, CRAN, the Web. All-in-One Download

Search by keywords in R packages, task views, CRAN, the web and display the results in the console or in txt, html or pdf files. Download the package documentation (html index, README, NEWS, pdf manual, vignettes, source code, binaries) with a single instruction. Visualize the package dependencies and CRAN checks. Compare the package versions, unload and install the packages and their dependencies in a safe order. Explore CRAN archives. Use the above functions for task view maintenance. Access web search engines from the console thanks to 80+ bookmarks. All functions accept standard and non-standard evaluation.

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3.40 score 10 scripts 630 downloads

CEDA - CRISPR Screen and Gene Expression Differential Analysis

Provides analytical methods for analyzing CRISPR screen data at different levels of gene expression. Multi-component normal mixture models and EM algorithms are used for modeling.

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3.40 score 3 scripts 285 downloads

msme - Functions and Datasets for "Methods of Statistical Model Estimation"

Functions and datasets from Hilbe, J.M., and Robinson, A.P. 2013. Methods of Statistical Model Estimation. Chapman & Hall / CRC.

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3.40 score 1 stars 4 dependents 207 scripts 702 downloads

stratification - Univariate Stratification of Survey Populations

Univariate stratification of survey populations with a generalization of the Lavallee-Hidiroglou method of stratum construction. The generalized method takes into account a discrepancy between the stratification variable and the survey variable. The determination of the optimal boundaries also incorporate, if desired, an anticipated non-response, a take-all stratum for large units, a take-none stratum for small units, and a certainty stratum to ensure that some specific units are in the sample. The well known cumulative root frequency rule of Dalenius and Hodges and the geometric rule of Gunning and Horgan are also implemented.

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3.39 score 2 dependents 41 scripts 857 downloads

mixture - Mixture Models for Clustering and Classification

An implementation of 14 parsimonious mixture models for model-based clustering or model-based classification. Gaussian, Student's t, generalized hyperbolic, variance-gamma or skew-t mixtures are available. All approaches work with missing data. Celeux and Govaert (1995) <doi:10.1016/0031-3203(94)00125-6>, Browne and McNicholas (2014) <doi:10.1007/s11634-013-0139-1>, Browne and McNicholas (2015) <doi:10.1002/cjs.11246>.

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gslopenblascppopenmp

3.39 score 1 stars 17 dependents 24 scripts 801 downloads

reaborn - Statistical Data Visualization, the 'seaborn' Way

An 'R' port of the 'Python' 'seaborn' library. 'reaborn' mirrors the 'seaborn' public function API (identical function names, argument names, and defaults) and renders visually indistinguishable plots using 'ggplot2'. Because every 'reaborn' plot is a 'ggplot' object, it can be extended with the full 'ggplot2' grammar of graphics.

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3.38 score 12 scripts

kidney.epi - Kidney-Related Functions for Clinical and Epidemiological Research

Contains kidney care oriented functions. Current version contains functions for calculation of: - Estimated glomerular filtration rate by CKD-EPI (2021 and 2009), MDRD, CKiD, FAS, EKFC, etc. - Kidney Donor Risk Index and Kidney Donor Profile Index for kidney transplant donors. - Citation: Bikbov B. kidney.epi: Kidney-Related Functions for Clinical and Epidemiological Research. Scientific-Tools.Org, <https://Scientific-Tools.Org>. <doi:10.32614/CRAN.package.kidney.epi>.

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3.38 score 16 scripts 637 downloads

deal - Learning Bayesian Networks with Mixed Variables

Bayesian networks with continuous and/or discrete variables can be learned and compared from data. The method is described in Boettcher and Dethlefsen (2003), <doi:10.18637/jss.v008.i20>.

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3.38 score 1 stars 48 scripts 338 downloads

oaxaca - Blinder-Oaxaca Decomposition

An implementation of the Blinder-Oaxaca decomposition for linear regression models.

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3.37 score 3 stars 77 scripts 1.0k downloads

graphicalVAR - Graphical VAR for Experience Sampling Data

Estimates within and between time point interactions in experience sampling data, using the Graphical vector autoregression model in combination with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.

Given an adjacency matrix drawn from a Generalized Stochastic Block Model with missing observations, this package robustly estimates the probabilities of connection between nodes and detects outliers nodes, as describes in Gaucher, Klopp and Robin (2019) <arXiv:1911.13122>.

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3.32 score 14 scripts 257 downloads

RADstackshelpR - Optimize the De Novo Stacks Pipeline via R

Offers a handful of useful wrapper functions which streamline the reading, analyzing, and visualizing of variant call format (vcf) files in R. This package was designed to facilitate an explicit pipeline for optimizing Stacks (Rochette et al., 2019) (<doi:10.1111/mec.15253>) parameters during de novo (without a reference genome) assembly and variant calling of restriction-enzyme associated DNA sequence (RADseq) data. The pipeline implemented here is based on the 2017 paper "Lost in Parameter Space" (Paris et al., 2017) (<doi:10.1111/2041-210X.12775>) which establishes clear recommendations for optimizing the parameters 'm', 'M', and 'n', during the process of assembling loci.

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3.32 score 42 scripts 192 downloads

fuser - Fused Lasso for High-Dimensional Regression over Groups

Enables high-dimensional penalized regression across heterogeneous subgroups. Fusion penalties are used to share information about the linear parameters across subgroups. The underlying model is described in detail in Dondelinger and Mukherjee (2017) <arXiv:1611.00953>.

mpwR - Standardized Comparison of Workflows in Mass Spectrometry-Based Bottom-Up Proteomics

Useful functions to analyze proteomic workflows including number of identifications, data completeness, missed cleavages, quantitative and retention time precision etc. Various software outputs are supported such as 'ProteomeDiscoverer', 'Spectronaut', 'DIA-NN' and 'MaxQuant'.

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3.30 score 8 scripts 209 downloads

sparseSEM - Elastic Net Penalized Maximum Likelihood for Structural Equation Models with Network GPT Framework

Provides elastic net penalized maximum likelihood estimator for structural equation models (SEM). The package implements `lasso` and `elastic net` (l1/l2) penalized SEM and estimates the model parameters with an efficient block coordinate ascent algorithm that maximizes the penalized likelihood of the SEM. Hyperparameters are inferred from cross-validation (CV). A Stability Selection (STS) function is also available to provide accurate causal effect selection. The software achieves high accuracy performance through a `Network Generative Pre-trained Transformer` (Network GPT) Framework with two steps: 1) pre-trains the model to generate a complete (fully connected) graph; and 2) uses the complete graph as the initial state to fit the `elastic net` penalized SEM.

hypergate - Machine Learning of Hyperrectangular Gating Strategies for High-Dimensional Cytometry

Given a high-dimensional dataset that typically represents a cytometry dataset, and a subset of the datapoints, this algorithm outputs an hyperrectangle so that datapoints within the hyperrectangle best correspond to the specified subset. In essence, this allows the conversion of clustering algorithms' outputs to gating strategies outputs.

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3.22 score 33 scripts 263 downloads

GoFKernel - Testing Goodness-of-Fit with the Kernel Density Estimator

Tests of goodness-of-fit based on a kernel smoothing of the data. References: Pavía (2015) <doi:10.18637/jss.v066.c01>.

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3.21 score 7 dependents 77 scripts 495 downloads

dendRoAnalyst - A Tool for Processing and Analyzing Dendrometer Data

There are various functions for managing and cleaning data before the application of different approaches. This includes identifying and erasing sudden jumps in dendrometer data not related to environmental change, identifying the time gaps of recordings, and changing the temporal resolution of data to different frequencies. Furthermore, the package calculates daily statistics of dendrometer data, including the daily amplitude of tree growth. Various approaches can be applied to separate radial growth from daily cyclic shrinkage and expansion due to uptake and loss of stem water. In addition, it identifies periods of consecutive days with user-defined climatic conditions in daily meteorological data, then check what trees are doing during that period.

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3.20 score 2 stars 40 scripts 621 downloads

eggCounts - Hierarchical Modelling of Faecal Egg Counts

An implementation of Bayesian hierarchical models for faecal egg count data to assess anthelmintic efficacy. Bayesian inference is done via MCMC sampling using 'Stan' <https://mc-stan.org/>.

mergersim - Merger Simulation and Calibration

Analyze mergers between firms. Models of competition include differentiated Bertrand price-setting, Nash bargaining, and second score auctions, as implemented in Panhans and Taragin (2023) <doi:10.1016/j.ijindorg.2023.102986>. Calibrates demand systems including standard logit, nested logit, and generalized nested logit as implemented in Panhans and Wiemer (2026) <doi:10.1093/joclec/nhaf037>.

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3.18 score 5 scripts

checktor - Extra CRAN Submission Checks

Provides automated checks for common Comprehensive R Archive Network (CRAN) submission issues that are not caught by standard 'R CMD check'. Consolidates ad-hoc requirements that CRAN reviewers enforce but standard checks do not surface, helping 'R' package maintainers identify and fix issues before submission to reduce rejection rates. Covers code-pattern issues, DESCRIPTION-field formatting, documentation problems, and general package structure concerns.

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quarto

3.18 score

testflow - A Workflow for Statistical Testing, Interpretation, and 'ggplot2'-Based Visualization

Provides a unified workflow for choosing, running, interpreting, and visualizing common statistical tests. The package combines assumption checks, test selection, effect sizes, formatted results, plain-language interpretation, and 'ggplot2'-based statistical visualizations. Implemented methods follow standard references including Casella and Berger (2002, ISBN:9780534243128), Hollander et al. (2013, ISBN:9781118553299), Agresti (2013, ISBN:9780470463635), and Cohen (1988, ISBN:9780805802832).

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3.18 score 1 scripts

climatehealth - Statistical Tools for Modelling Climate-Health Impacts

Tools for producing climate-health indicators and supporting official statistics from health and climate data. Implements analytical workflows for temperature-related mortality, wildfire smoke exposure, air pollution, suicides related to extreme heat, malaria, and diarrhoeal disease outcomes, with utilities for descriptive statistics, model validation, attributable fraction and attributable number estimation, relative risk estimation, minimum mortality temperature estimation, and plotting for reporting. These six indicators are endorsed by the United Nations Statistical Commission for inclusion in the Global Set of Environment and Climate Change Statistics. Implemented methods include distributed lag non-linear models (DLNM), quasi-Poisson time-series regression, case-crossover analysis, Bayesian spatio-temporal models using the Integrated Nested Laplace Approximation ('INLA'), and multivariate meta-analysis for sub-national estimates. The package is based on methods developed in the Standards for Official Statistics on Climate-Health Interactions (SOSCHI) project <https://climate-health.officialstatistics.org>. For methodologies, see Watkins et al. (2026) <doi:10.5281/zenodo.14865904>, Jose et al. (2026) <doi:10.5281/zenodo.14052183>, Pearce et al. (2026) <doi:10.5281/zenodo.14050224>, Byukusenge et al. (2026) <doi:10.5281/zenodo.15585042>, Dzakpa et al. (2026) <doi:10.5281/zenodo.14881886>, and Dzakpa et al. (2026) <doi:10.5281/zenodo.14871506>.

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3.18 score 10 scripts 493 downloads

pubchem.bio - Biologically Informed Metabolomic Libraries from 'PubChem'

All 'PubChem' compounds are downloaded to a local computer, but for each compound, only partial records are used. The data are organized into small files referenced by 'PubChem' CID. This package also contains functions to parse the biologically relevant compounds from all 'PubChem' compounds, using biological database sources, pathway presence, and taxonomic relationships. Taxonomy is used to generate a lowest common ancestor taxonomy ID (NCBI) for each biological metabolite, which then enables creation of taxonomically specific metabolome databases for any taxon.

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openjdk

3.18 score 5 scripts 254 downloads

recforest - Random Survival Forest for Recurrent Events

A tool designed to analyze recurrent events when dealing with right-censored data and the potential presence of a terminal event (that prevents further occurrences, like death). It extends the random survival forest algorithm, adapting splitting rules and node estimators to handle complexities of recurrent events. The methodology is fully described in Murris, J., Bouaziz, O., Jakubczak, M., Katsahian, S., & Lavenu, A. (2024) (<https://hal.science/hal-04612431v1/document>).

Functions for working with code lists and vectors with codes. These are an alternative for factor that keep track of both the codes and labels. Methods allow for transforming between codes and labels. Also supports hierarchical code lists.

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3.13 score 27 scripts 130 downloads

bgw - Bunch-Gay-Welsch Statistical Estimation

Performs statistical estimation and inference-related computations by accessing and executing modified versions of 'Fortran' subroutines originally published in the Association for Computing Machinery (ACM) journal Transactions on Mathematical Software (TOMS) by Bunch, Gay and Welsch (1993) <doi:10.1145/151271.151279>. The acronym 'BGW' (from the authors' last names) will be used when making reference to technical content (e.g., algorithm, methodology) that originally appeared in ACM TOMS. A key feature of BGW is that it exploits the special structure of statistical estimation problems within a trust-region-based optimization approach to produce an estimation algorithm that is much more effective than the usual practice of using optimization methods and codes originally developed for general optimization. The 'bgw' package bundles 'R' wrapper (and related) functions with modified 'Fortran' source code so that it can be compiled and linked in the 'R' environment for fast execution. This version implements a function ('bgw_mle.R') that performs maximum likelihood estimation (MLE) for a user-provided model object that computes probabilities (a.k.a. probability densities). The original motivation for producing this package was to provide fast, efficient, and reliable MLE for discrete choice models that can be called from the 'Apollo' choice modelling 'R' package ( see <https://www.apollochoicemodelling.com>). Starting with the release of Apollo 3.0, BGW is the default estimation package. However, estimation can also be performed using BGW in a stand-alone fashion without using 'Apollo' (as shown in simple examples included in the package). Note also that BGW capabilities are not limited to MLE, and future extension to other estimators (e.g., nonlinear least squares, generalized method of moments, etc.) is possible. The 'Fortran' code included in 'bgw' was modified by one of the original BGW authors (Bunch) under his rights as confirmed by direct consultation with the ACM Intellectual Property and Rights Manager. See <https://authors.acm.org/author-resources/author-rights>. The main requirement is clear citation of the original publication (see above).

RRgeo - Species Distribution Modelling for Rare Species

Performs species distribution modeling for rare species with unprecedented accuracy (Mondanaro et al., 2023 <doi:10.1111/2041-210X.14066>) and finds the area of origin of species and past contact between them taking climatic variability in full consideration (Mondanaro et al., 2025 <doi:10.1111/2041-210X.14478>).

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3.11 score 16 scripts 505 downloads

spcosa - Spatial Coverage Sampling and Random Sampling from Compact Geographical Strata

Spatial coverage sampling and random sampling from compact geographical strata created by k-means. See Walvoort et al. (2010) <doi:10.1016/j.cageo.2010.04.005> for details.

Cluster-independent method based on topology structure of gene co-expression network for identifying feature gene sets, extracting cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Without prior cell clustering, SifiNet circumvents potential inaccuracies in clustering that may influence subsequent analyses. This method is introduced in Qi Gao, Zhicheng Ji, Liuyang Wang, Kouros Owzar, Qi-Jing Li, Cliburn Chan, Jichun Xie "SifiNet: a robust and accurate method to identify feature gene sets and annotate cells" (2024) <doi:10.1093/nar/gkae307>.

Calculates centrality indices additional to the 'igraph' package centrality functions.

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3.02 score 1 stars 1 dependents 88 scripts 465 downloads

GenderInfer - This is a Collection of Functions to Analyse Gender Differences

Implementation of functions, which combines binomial calculation and data visualisation, to analyse the differences in publishing authorship by gender described in Day et al. (2020) <doi:10.1039/C9SC04090K>. It should only be used when self-reported gender is unavailable.

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3.02 score 21 scripts 222 downloads

causaldrf - Estimating Causal Dose Response Functions

Functions and data to estimate causal dose response functions given continuous, ordinal, or binary treatments. A description of the methods is given in Galagate (2016) <https://drum.lib.umd.edu/handle/1903/18170>.

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3.02 score 4 stars 26 scripts 257 downloads

tidysynth - A Tidy Implementation of the Synthetic Control Method

A synthetic control offers a way of evaluating the effect of an intervention in comparative case studies. The package makes a number of improvements when implementing the method in R. These improvements allow users to inspect, visualize, and tune the synthetic control more easily. A key benefit of a tidy implementation is that the entire preparation process for building the synthetic control can be accomplished in a single pipe.

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3.01 score 203 scripts 1.0k downloads

nephro - Utilities for Nephrology

Set of functions to estimate kidney function and other traits of interest in nephrology.

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3.01 score 4 stars 17 scripts 316 downloads

lmomRFA - Regional Frequency Analysis using L-Moments

Functions for regional frequency analysis using the methods of J. R. M. Hosking and J. R. Wallis (1997), "Regional frequency analysis: an approach based on L-moments".

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glibc

3.01 score 1 stars 1 dependents 34 scripts 563 downloads

mixedsubjects - Causal Inference in Experiments with Mixed-Subjects Designs

Implements seven estimators for average treatment effect (ATE) estimation in mixed-subjects designs (MSDs), where human subjects data is augmented with predictions from large language models (LLMs). Includes Difference-in-Means, GREG, PPI++, Doubly-Tuned, Difference-in-Predictions (DiP), DiP++, and D-T DiP estimators. Provides point estimates, variance estimation via delta-method or bootstrap, and optimal design selection for budget allocation between human observations and LLM predictions.

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3.00 score 2 scripts

NeighborFinder - Find Neighbor Species of a Bacteria of Interest in the Human Gut Microbiota

Implementation of the local approach described in Sola et al., 2026 <doi:10.64898/2025.12.05.692507> to identify companion species of a bacteria of interest. From several abundance tables of metagenomic data, 'NeighborFinder' suggests a shortlist of companion species based on the integration of results. A visualization via a network is proposed.

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3.00 score

respondeR - Imputing Responder Proportions from Continuous Outcomes

Express meta-analyses of continuous trial outcomes in terms of responder risks, following the interpretability tutorial of Thorlund, Walter, Johnston, Furukawa and Guyatt (2011) <doi:10.1002/jrsm.46>. Given the mean change, standard deviation and sample size per arm across studies, respondeR estimates the proportion of patients who cross a minimal important difference (MID) threshold under a parametric model for the change scores, and contrasts the arms as a risk difference, risk ratio, odds ratio or number needed to treat. It provides median, unweighted-mean, weighted-mean and per-study (fixed- or random-effects) pooling, the standardized-mean-difference to odds-ratio bridge of Anzures-Cabrera, Sarpatwari and Higgins (2011) <doi:10.1002/sim.4298>, a threshold-free common-language effect size, and a point-and-click 'Shiny' application. The estimation methods were evaluated in a simulation study by Sofi-Mahmudi (2024) <https://hdl.handle.net/11375/30210>.

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3.00 score 5 scripts

hydrocan - Unified Access to Canadian Hydrometric Data

Provides a unified interface for accessing diverse web-published hydrometric data sources across Canada, presenting users with consistent tabular output regardless of the underlying data source.

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3.00 score 5 scripts

DICErClust - Deep Significance Clustering for Clinical Risk Stratification

We provide an R implementation of Deep Significance Clustering (DICE), a self-supervised learning framework designed to identify clinically meaningful and risk-stratified patient subgroups from electronic health record (EHR) data. DICE jointly optimizes deep representation learning, clustering, and outcome prediction while enforcing statistical significance between predicted outcomes and cluster membership. This integrated optimization produces subgroups that are both clinically coherent and predictive, addressing a gap where traditional unsupervised clustering methods and supervised risk prediction models alone may fail to generate actionable clinical groupings. See Huang et al. (2021) <doi:10.1093/jamia/ocab203>.

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3.00 score 416 downloads

fcmfd - Fuzzy C-Means for Fuzzy Data

Implements a fuzzy clustering approach for ordinal Likert-type data using triangular fuzzy numbers (TFNs). The package extends the classical fuzzy C-means algorithm to better handle uncertainty in ordinal scales and includes automatic selection of the number of clusters using the Xie-Beni validity index. References: Coppi, R., D'Urso, P., and Giordani, P. (2012), "Fuzzy and possibilistic clustering for fuzzy data", <doi:10.1016/j.csda.2010.09.013>. Xie, X. L. and Beni, G. (1991), "A validity measure for fuzzy clustering", <doi:10.1109/34.85677>.

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3.00 score 388 downloads

poissonsuperlearner - Poisson Super Learner

Provides tools for fitting piecewise-constant hazard models for survival and competing risks data, including ensemble hazard estimation via the Super Learner framework. The package supports estimation of survival functions and absolute risk predictions from fitted cause-specific hazard models. For the Super Learner framework see van der Laan, Polley and Hubbard (2007) <doi:10.2202/1544-6115.1309>.

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cpp

3.00 score 3 scripts 503 downloads

ume - Ultrahigh-Resolution Mass Spectrometry Data Evaluation for Complex Organic Matter

Provides tools for assigning molecular formulas from exact masses obtained by ultrahigh-resolution mass spectrometry. The methodology follows the workflow described in Leefmann et al. (2019) <doi:10.1002/rcm.8315>. The package supports the inspection, filtering and visualization of molecular formula data and includes utilities for calculating common molecular parameters (e.g., double bond equivalents, DBE). A graphical user interface is available via the 'shiny'-based 'ume' application.

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3.00 score 468 downloads

diagFDR - Verifiable FDR Diagnostics for Proteomics

Provides methods to compute verifiable false discovery rate (FDR) diagnostic checks for workflows based on target-decoy competition and related confidence measures. Implements calibration, stability and tail diagnostics, including tail support, threshold elasticity, posterior error probability (PEP) reliability, and equal-chance checks. If you used this package in your research, please cite the associated preprint <doi:10.64898/2026.04.16.718468>. Detailed examples of using this package can also be found on the GitHub repository (<https://github.com/Jacky11/diagFDR>).

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3.00 score 521 downloads

funMoDisco - Motif Discovery in Functional Data

Efficiently implementing two complementary methodologies for discovering motifs in functional data: ProbKMA and FunBIalign. Cremona and Chiaromonte (2023) "Probabilistic K-means with Local Alignment for Clustering and Motif Discovery in Functional Data" <doi:10.1080/10618600.2022.2156522> is a probabilistic K-means algorithm that leverages local alignment and fuzzy clustering to identify recurring patterns (candidate functional motifs) across and within curves, allowing different portions of the same curve to belong to different clusters. It includes a family of distances and a normalization to discover various motif types and learns motif lengths in a data-driven manner. It can also be used for local clustering of misaligned data. Di Iorio, Cremona, and Chiaromonte (2023) "funBIalign: A Hierarchical Algorithm for Functional Motif Discovery Based on Mean Squared Residue Scores" <doi:10.48550/arXiv.2306.04254> applies hierarchical agglomerative clustering with a functional generalization of the Mean Squared Residue Score to identify motifs of a specified length in curves. This deterministic method includes a small set of user-tunable parameters. Both algorithms are suitable for single curves or sets of curves. The package also includes a flexible function to simulate functional data with embedded motifs, allowing users to generate benchmark datasets for validating and comparing motif discovery methods.

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openblascppopenmp

3.00 score 1 scripts 569 downloads

hybridEHR - Synthetic Hybrid Electronic Health Record Generation for SARS-Related Research and CT Views

Generates synthetic electronic health record data, including patients, encounters, vitals, laboratory results, medications, procedures, and allergies. The package supports optional SARS-focused and computed tomography (CT) research views and export to CSV, SQLite, and Excel formats for research and development workflows.

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3.00 score 441 downloads

Provides functions to perform the Sequential Probability Ratio Test (SPRT) for hypothesis testing in Binomial, Poisson and Normal distributions. The package allows users to specify Type I and Type II error probabilities, decision thresholds, and compare null and alternative hypotheses sequentially as data accumulate. It includes visualization tools for plotting the likelihood ratio path and decision boundaries, making it easier to interpret results. The methods are based on Wald (1945) <doi:10.1214/aoms/1177731118>, who introduced the SPRT as one of the earliest and most powerful sequential analysis techniques. This package is useful in quality control, clinical trials, and other applications requiring early decision-making.The term 'SPRT' is an abbreviation and used intentionally.

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3.00 score 9 scripts 485 downloads

gmGeostats - Geostatistics for Compositional Analysis

Support for geostatistical analysis of multivariate data, in particular data with restrictions, e.g. positive amounts, compositions, distributional data, microstructural data, etc. It includes descriptive analysis and modelling for such data, both from a two-point Gaussian perspective and multipoint perspective. The methods mainly follow Tolosana-Delgado, Mueller and van den Boogaart (2018) <doi:10.1007/s11004-018-9769-3>.

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openmp

3.00 score 1 stars 8 scripts 258 downloads

vmTools - Version Management Tools on the File System

Data version management on the file system for smaller projects. Manage data pipeline outputs with symbolic folder links, structured logging and reports, using 'R6' classes for encapsulation and 'data.table' for speed. Directory-specific logs used as source of truth to allow portability of versioned data folders.

Estimation of Markov generator matrices from discrete-time observations. The implemented approaches comprise diagonal and weighted adjustment of matrix logarithm based candidate solutions as in Israel (2001) <doi:10.1111/1467-9965.00114> as well as a quasi-optimization approach. Moreover, the expectation-maximization algorithm and the Gibbs sampling approach of Bladt and Sorensen (2005) <doi:10.1111/j.1467-9868.2005.00508.x> are included.

Manipulate data through memory-mapped files, as vectors, matrices or arrays. Basic arithmetic functions are implemented, but currently no matrix arithmetic. Can write and read descriptor files for compatibility with the 'bigmemory' package.

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cpp

2.95 score 1 dependents 177 downloads

tinydng - 'TinyDNG' C++ Header Files

Provides C++ header files for 'TinyDNG', a small header-only library for reading and writing 'DNG' and 'TIFF' files.

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2.95 score 6 dependents

GCalcium - A Data Manipulation and Analysis Package for Calcium Indicator Data

Provides shortcuts in extracting useful data points and summarizing waveform data. It is optimized for speed to work efficiently with large data sets so you can get to the analysis phase more quickly. It also utilizes a user-friendly format for use by both beginners and seasoned R users.

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2.95 score 18 scripts 47 downloads

pgdraw - Generate Random Samples from the Polya-Gamma Distribution

Generates random samples from the Polya-Gamma distribution using an implementation of the algorithm described in J. Windle's PhD thesis (2013) <https://repositories.lib.utexas.edu/bitstream/handle/2152/21842/WINDLE-DISSERTATION-2013.pdf>. The underlying implementation is in C.

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cpp

2.95 score 6 dependents 49 scripts 665 downloads

Expectile and quantile regression of models with nonlinear effects e.g. spatial, random, ridge using least asymmetric weighed squares / absolutes as well as boosting; also supplies expectiles for common distributions.

Provides tools for conditional and spatially dependent density estimation using Spatial Logistic Gaussian Processes (SLGPs). The approach represents probability densities through finite-rank Gaussian process priors transformed via a spatial logistic density transformation, enabling flexible non-parametric modeling of heterogeneous data. Functionality includes density prediction, quantile and moment estimation, sampling methods, and preprocessing routines for basis functions. Applications arise in spatial statistics, machine learning, and uncertainty quantification. The methodology builds on the framework of Leonard (1978) <doi:10.1111/j.2517-6161.1978.tb01655.x>, Lenk (1988) <doi:10.1080/01621459.1988.10478625>, Tokdar (2007) <doi:10.1198/106186007X210206>, Tokdar (2010) <doi:10.1214/10-BA605>, and is further aligned with recent developments in Bayesian non-parametric modelling: see Gautier (2023) <https://boristheses.unibe.ch/4377/>, and Gautier (2025) <doi:10.48550/arXiv.2110.02876>).

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cpp

2.86 score 12 scripts 181 downloads

EDISON - Network Reconstruction and Changepoint Detection

Package EDISON (Estimation of Directed Interactions from Sequences Of Non-homogeneous gene expression) runs an MCMC simulation to reconstruct networks from time series data, using a non-homogeneous, time-varying dynamic Bayesian network. Networks segments and changepoints are inferred concurrently, and information sharing priors provide a reduction of the inference uncertainty.

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2.80 score 2 stars 1 dependents 15 scripts 507 downloads

matchMulti - Optimal Multilevel Matching using a Network Algorithm

Performs multilevel matches for data with cluster- level treatments and individual-level outcomes using a network optimization algorithm. Functions for checking balance at the cluster and individual levels are also provided, as are methods for permutation-inference-based outcome analysis. Details in Pimentel et al. (2018) <doi:10.1214/17-AOAS1118>. The optmatch package, which is useful for running many of the provided functions, may be downloaded from Github at <https://github.com/markmfredrickson/optmatch> if not available on CRAN.

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2.80 score 1 stars 1 dependents 21 scripts 701 downloads

mAr - Multivariate AutoRegressive Analysis

R functions for the estimation and eigen-decomposition of multivariate autoregressive models.

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2.80 score 1 stars 2 dependents 105 scripts 445 downloads

dcov - A Fast Implementation of Distance Covariance

Efficient methods for computing distance covariance and relevant statistics. See Székely et al.(2007) <doi:10.1214/009053607000000505>; Székely and Rizzo (2013) <doi:10.1016/j.jmva.2013.02.012>; Székely and Rizzo (2014) <doi:10.1214/14-AOS1255>; Huo and Székely (2016) <doi:10.1080/00401706.2015.1054435>.

AlphaPart - Partition/Decomposition of Breeding Values by Paths of Information

A software that implements a method for partitioning genetic trends to quantify the sources of genetic gain in breeding programmes. The partitioning method is described in Garcia-Cortes et al. (2008) <doi:10.1017/S175173110800205X>. The package includes the main function AlphaPart for partitioning breeding values and auxiliary functions for manipulating data and summarizing, visualizing, and saving results.

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cpp

2.75 score 28 scripts 423 downloads

vbm - Variance-Based Sensitivity Analysis for Weighting Estimators

Provides methods for variance-based sensitivity analysis and weighting estimators in observational studies based on methodology by Huang & Pimentel (2025) <doi:10.1093/biomet/asae040>. Includes bootstrap inference, bias bounds estimation, and visualization tools for sensitivity parameters.

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2.75 score 56 scripts

QTLRel - Tools for Mapping of Quantitative Traits of Genetically Related Individuals and Calculating Identity Coefficients from Pedigrees

This software provides tools for quantitative trait mapping in populations such as advanced intercross lines where relatedness among individuals should not be ignored. It can estimate background genetic variance components, impute missing genotypes, simulate genotypes, perform a genome scan for putative quantitative trait loci (QTL), and plot mapping results. It also has functions to calculate identity coefficients from pedigrees, especially suitable for pedigrees that consist of a large number of generations, or estimate identity coefficients from genotypic data in certain circumstances.

Functions to fit finite mixture of scale mixture of skew-normal (FM-SMSN) distributions, details in Prates, Lachos and Cabral (2013) <doi: 10.18637/jss.v054.i12>, Cabral, Lachos and Prates (2012) <doi:10.1016/j.csda.2011.06.026> and Basso, Lachos, Cabral and Ghosh (2010) <doi:10.1016/j.csda.2009.09.031>.

Implementations for several robust procedures that allow for (online) extraction of the signal of univariate or multivariate time series by applying robust regression techniques to a moving time window are provided. Included are univariate filtering procedures based on repeated-median regression as well as hybrid and trimmed filters derived from it; see Schettlinger et al. (2006) <doi:10.1515/BMT.2006.010>. The adaptive online repeated median by Schettlinger et al. (2010) <doi:10.1002/acs.1105> and the slope comparing adaptive repeated median by Borowski and Fried (2013) <doi:10.1007/s11222-013-9391-7> choose the width of the moving time window adaptively. Multivariate versions are also provided; see Borowski et al. (2009) <doi:10.1080/03610910802514972> for a multivariate online adaptive repeated median and Borowski (2012) <doi:10.17877/DE290R-14393> for a multivariate slope comparing adaptive repeated median. Furthermore, a repeated-median based filter with automatic outlier replacement and shift detection is provided; see Fried (2004) <doi:10.1080/10485250410001656444>.

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cpp

2.70 score 2 stars 29 scripts 2.2k downloads

apifetch - Token-Authenticated REST API Retrieval Toolkit

A small, dependency-light toolkit for talking to token-authenticated REST APIs. It manages authentication tokens in process environment variables (never written to disk), builds requests with configurable authentication and pagination strategies, and retrieves paginated data either one page at a time or in chunks combined into a single tibble. The design is API-agnostic: a single 'apifetch_api' profile describes an endpoint together with how it authenticates and paginates, so the same verbs work across different services.

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2.70 score 1 scripts

peeky - Download and Extract 'shinylive' Applications

Peek into published 'shinylive' applications by retrieving their source code. Supports downloading and extracting 'shiny' application source from 'quarto' documents and standalone 'shinylive' applications.

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quarto

2.70 score

deaviz - Visualization of Data Envelopment Analysis Problems

High-dimensional visualization methods for data envelopment analysis (DEA), gathering in one place techniques that have appeared in the literature but remained scattered and largely unimplemented: cross-efficiency matrix unfolding, the Porembski network with lambda edges, principal component analysis biplots, multidimensional-scaling colour-plots, self-organizing maps, the Costa bi-dimensional efficient frontier, parallel coordinates, radar charts, panel-data trajectory biplots, peer and reference networks, and a set of descriptive plots. The package is built around a single validated dea_data() object and uses the 'Benchmarking' package as its DEA engine. The implemented methods draw on a body of literature; representative references include Doyle and Green (1994) <doi:10.1057/jors.1994.84>, Porembski, Breitenstein and Alpar (2005) <doi:10.1007/s11123-005-1328-5> and Bana e Costa, Soares de Mello and Angulo Meza (2016) <doi:10.1016/j.ejor.2016.05.012>.

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2.70 score

araponga - Estimate 3D Orientations from 2D Landmarks

Estimates possible 3D orientations of an object from the 2D image coordinates of two landmarks and an approximate camera-object elevation angle. Because a projected 2D angle can be compatible with multiple 3D pitch, yaw, and view-elevation angles, the package returns compatible sets of orientations rather than a single unconstrained estimate.

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2.70 score

palsr - Projected Actor Locations for Spatial Interaction Modeling

Implements the Projected Actor Locations (PALS) method for spatial modeling of dyadic interactions between geographically mobile actors, as described in Kim, Liu and Desmarais (2023) <doi:10.1017/psrm.2022.6>. PALS applies exponential-smoothing weights to the spatiotemporal histories of a focal actor and its interaction partners ("alters") to project the location of future interactions. The package provides projection, maximum-similarity parameter estimation by minimizing great-circle (Haversine) prediction error, nonparametric bootstrap with multiple-imputation (Rubin's Rules) pooling, dyadic distance covariate construction, visualization, and a simulated example dataset of subnational conflict.

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cpp

2.70 score

saeHB.Spatial.Beta - Small Area Estimation Hierarchical Bayes for Spatial Beta Model

Provides several functions and datasets for area-level Small Area Estimation using the Hierarchical Bayesian (HB) method. Model-based estimators are designed for variables of interest that follow a Beta distribution. The package supports spatial structures under the Simultaneous Autoregressive (SAR) and Leroux Conditional Autoregressive (CAR) models, accommodating survey design effect (DEFF) adjustments. The 'rjags' package is employed to obtain parameter estimates via Gibbs Sampling. For references, see Rao and Molina (2015) <doi:10.1002/9781118735855>, Kubacki and Jedrzejczak (2016) <doi:10.59170/stattrans-2016-022>, Leroux et al. (2000) <doi:10.1007/978-1-4612-1284-3_4>, and Chung and Datta (2020) <https://www.census.gov/content/dam/Census/library/working-papers/2020/adrm/RRS2020-07.pdf>.

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jagscpp

2.70 score

evbsreg - Local Influence Diagnostics for the Extreme-Value Birnbaum-Saunders Regression Model

Implements local influence diagnostics for the Extreme-Value Birnbaum-Saunders (EVBS) regression model: joint maximum likelihood estimation, conformal normal curvature diagnostics under three perturbation schemes (case-weight, response variable, and explanatory variable), randomized quantile residuals with simulation envelope, Monte Carlo simulation utilities, and publication-quality density and diagnostic plots. The methods are described in Ospina, Lima, Barros, and Macedo (2026, submitted) and are applied to monthly maximum wind gust data from Itajai, Brazil.

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2.70 score

muse - Multiple Unobserved Sources of Error State Space Models

Implements the Power / Trend / Seasonal (PTS) model, a unified state-space framework based on the Multiple Source of Error (MSOE) model. It brings the trend, seasonal and irregular component models of Harvey (1989) <doi:10.1017/CBO9781107049994>, Durbin and Koopman (2012) <doi:10.1093/acprof:oso/9780199641178.001.0001>, Proietti (2000) <doi:10.1016/S0169-2070(00)00037-6>, Sbrana and Silvestrini (2023) <doi:10.1016/j.ijforecast.2022.03.003> and others together under a single estimation, selection and forecasting interface, with an optional Box-Cox power transformation. Models are estimated by maximum likelihood through the Kalman filter and smoother, with automatic component selection by information criteria.

Tests whether multivariate ordinal data may stem from discretizing a multivariate normal distribution. The test is described by Foldnes and Grønneberg (2019) <doi:10.1080/10705511.2019.1673168>. In addition, an adjusted polychoric correlation estimator is provided that takes marginal knowledge into account, as described by Grønneberg and Foldnes (2022) <doi:10.1037/met0000495>.

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2.70 score 1 scripts 193 downloads

spDBL - Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models

Provides tools for Bayesian learning of spatiotemporal dynamical mechanistic models. Includes methods for parameter estimation, simulation, and inference using hierarchical and state-space modeling approaches, following Banerjee, Chen, Frankenburg and Zhou (2025) <https://jmlr.org/papers/v26/22-0896.html>.

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cpp

2.70 score

onnxr - Bindings to 'ONNX' Runtime

Provides native access to the 'Open Neural Network Exchange' (ONNX) Runtime <https://onnxruntime.ai/>, which is a performant engine for running machine learning models that are saved to a standardized format. Rather than interfacing with 'ONNX' via 'Python', as in the official 'onnx' package, 'onnxr' directly interfaces with the runtime's 'C++' API via 'cpp11'. Models saved to '.onnx' files can be loaded and run on various backends, including CPUs and Apple's 'CoreML' library.

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cpp

2.70 score 4 scripts

lisat - Longitudinal Integration Site Analysis Toolkit

A comprehensive toolkit for the analysis of longitudinal integration site data, including data cleaning, quality control, statistical modeling, and visualization. It streamlines the entire workflow of integration site analysis, supports simple input formats, and provides user-friendly functions for researchers in virus integration site analysis. Ni et al. (2025) <doi:10.64898/2025.12.20.695672>.

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2.70 score 400 downloads

SEPA - Segment Profile Extraction via Pattern Analysis

Implements the Segment Profile Extraction via Pattern Analysis method for row-mean-centered multivariate data. Core capabilities include SVD-based row-isometric biplot construction, bias-corrected and accelerated, and percentile bootstrap confidence intervals for domain coordinates and per-person direction cosines, Procrustes alignment of bootstrap replicates across planes, parallel analysis for dimensionality selection, and segment profile reconstruction in planes defined by pairs of singular dimensions. A synthetic Woodcock-Johnson IV look-alike dataset is provided for examples and testing. The method is described in Kim and Grochowalski (2019) <doi:10.1007/s00357-018-9277-7>.

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2.70 score 4 scripts 480 downloads

vcfheader - Fast Genetic Variant Call Format File Header Intelligence and Audit

Streams and parses variant call format file headers without reading full files. Provides structured metadata, validation, inference, and HTML reporting. For details on the specifications used see Danecek et al. (2021) <doi:10.1093/gigascience/giab008>.

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2.70 score 2 scripts 119 downloads

alpha.correction.bh - Benjamini-Hochberg Alpha Correction

Provides the alpha-adjustment correction from "Benjamini, Y., & Hochberg, Y. (1995) <doi:10.1111/j.2517-6161.1995.tb02031.x> Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 57(1), 289-300". For researchers interested in using the exact mathematical formulas and procedures as used in the original paper.

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2.70 score 5 scripts 250 downloads

archipelago - Visualising Variant Set Association Test Results

Provides a graphical method for joint visualisation of Variant Set Association Test (VSAT) results and individual variant association statistics. The Archipelago method assigns genomic coordinates to variant set statistics, allowing simultaneous display of variant-level and set-level signals in a unified plot. This supports interpretation of both collective and individual variant contributions in genetic association studies using variant aggregation approaches. For more see Lawless et al. (2026) <doi:10.1002/gepi.70025>.

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2.70 score 6 scripts 197 downloads

appraise - Bias-Aware Evidence Synthesis in Systematic Reviews

Implements a bias-aware framework for evidence synthesis in systematic reviews and health technology assessments, as described in Kabali (2025) <doi:10.1111/jep.70272>. The package models study-level effect estimates by explicitly accounting for multiple sources of bias through prior distributions and propagates uncertainty using posterior simulation. Evidence across studies is combined using posterior mixture distributions rather than a single pooled likelihood, enabling probabilistic inference on clinically or policy-relevant thresholds. The methods are designed to support transparent decision-making when study relevance and bias vary across the evidence base.

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2.70 score 1 scripts 177 downloads

emcAdr - Evolutionary Version of the Metropolis-Hastings Algorithm

Provides computational methods for detecting adverse high-order drug interactions from individual case safety reports using statistical techniques, allowing the exploration of higher-order interactions among drug cocktails.

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cppopenmp

2.70 score 1 scripts 162 downloads

mmtdiff - Moment-Matching Approximation for t-Distribution Differences

Implements the moment-matching approximation for differences of non-standardized t-distributed random variables in both univariate and multivariate settings. The package provides density, distribution function, quantile function, and random generation for the approximated distributions of t-differences. The methodology establishes the univariate approximated distributions through the systematic matching of the first, second, and fourth moments, and extends it to multivariate cases, considering both scenarios of independent components and the more general multivariate t-distributions with arbitrary dependence structures. Methods build on the classical moment-matching approximation method (e.g., Casella and Berger (2024) <doi:10.1201/9781003456285>).

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2.70 score 115 downloads

scaRabee - Optimization Toolkit for Pharmacokinetic-Pharmacodynamic Models

A port of the Scarabee toolkit originally written as a Matlab-based application. scaRabee provides a framework for simulation and optimization of pharmacokinetic-pharmacodynamic models at the individual and population level. It is built on top of the neldermead package, which provides the direct search algorithm proposed by Nelder and Mead for model optimization.

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2.70 score 3 scripts 195 downloads

Provides an end-to-end workflow for integrative analysis of two omics layers using sparse canonical correlation analysis (sCCA), including sample alignment, feature selection, network edge construction, and visualization of gene-metabolite relationships. The underlying methods are based on penalized matrix decomposition and sparse CCA (Witten, Tibshirani and Hastie (2009) <doi:10.1093/biostatistics/kxp008>), with design principles inspired by multivariate integrative frameworks such as mixOmics (Rohart et al. (2017) <doi:10.1371/journal.pcbi.1005752>).

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2.70 score 6 scripts 475 downloads

FGLMtrunc - Truncated Functional Generalized Linear Models

An implementation of the methodologies described in Xi Liu, Afshin A. Divani, and Alexander Petersen (2022) <doi:10.1016/j.csda.2022.107421>, including truncated functional linear and truncated functional logistic regression models.

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openblascppopenmp

2.70 score 3 scripts 244 downloads

GridOnClusters - Multivariate Joint Grid Discretization

Discretize multivariate continuous data using a grid to capture the joint distribution that preserves clusters in original data. It can handle both labeled or unlabeled data. Both published methods (Wang et al 2020) <doi:10.1145/3388440.3412415> and new methods are included. Joint grid discretization can prepare data for model-free inference of association, function, or causality.

Provides a comprehensive set of tools for working with order statistics, including functions for simulating order statistics, censored samples (Type I and Type II), and record values from various continuous distributions. Additionally, it offers functions to compute moments (mean, variance, skewness, kurtosis) of order statistics for several continuous distributions. These tools assist researchers and statisticians in understanding and analyzing the properties of order statistics and related data. The methods and algorithms implemented in this package are based on several published works, including Ahsanullah et al (2013, ISBN:9789491216831), Arnold and Balakrishnan (2012, ISBN:1461236444), Harter and Balakrishnan (1996, ISBN:9780849394522), Balakrishnan and Sandhu (1995) <doi:10.1080/00031305.1995.10476150>, Genç (2012) <doi:10.1007/s00362-010-0320-y>, Makouei et al (2021) <doi:10.1016/j.cam.2021.113386> and Nagaraja (2013) <doi:10.1016/j.spl.2013.06.028>.

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2.70 score 1 scripts 129 downloads

limonaid - Working with 'LimeSurvey' Surveys and Responses

'LimeSurvey' is Free/Libre Open Source Software for the development and administrations of online studies, using sophisticated tailoring capabilities to support multiple study designs (see <https://www.limesurvey.org>). This package supports programmatic creation of surveys that can then be imported into 'LimeSurvey', as well as user friendly import of responses from 'LimeSurvey' studies.

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2.70 score 1 stars 7 scripts 566 downloads

spotr - Estimate Spatial Population Indices from Ecological Abundance Data

Compute relative or absolute population trends across space and time using predictions from models fitted to ecological population abundance data, as described in Knape (2025) <doi:10.1016/j.ecolind.2025.113435>. The package supports models fitted by 'mgcv' or 'brms', and draws from posterior predictive distributions.

Provides statistical tools for analyzing net and relative survival, with a key feature of relaxing the assumption of independent censoring and incorporating the effect of dependent competing risks. It employs a copula-based methodology, specifically the Archimedean copula, to simulate data, conduct survival analysis, and offer comparisons with other methods. This approach is detailed in the work of Adatorwovor et al. (2022) <doi:10.1515/ijb-2021-0016>.

'Google Trends' provides cross-sectional and time-series data on searches, but lacks readily available longitudinal data. Researchers, who want to create longitudinal 'Google Trends' on their own, face practical challenges, such as normalized counts that make it difficult to combine cross-sectional and time-series data and limitations in data formats and timelines that limit data granularity over extended time periods. This package addresses these issues and enables researchers to generate longitudinal 'Google Trends' data. This package is built on 'pytrends', a Python library that acts as the unofficial 'Google Trends API' to collect 'Google Trends' data. As long as the 'Google Trends API', 'pytrends' and all their dependencies are working, this package will work. During testing, we noticed that for the same input (keyword, topic, data_format, timeline), the output index can vary from time to time. Besides, if the keyword is not very popular, then the resulting dataset will contain a lot of zeros, which will greatly affect the final result. While this package has no control over the accuracy or quality of 'Google Trends' data, once the data is created, this package coverts it to longitudinal data. In addition, the user may encounter a 429 Too Many Requests error when using cross_section() and time_series() to collect 'Google Trends' data. This error indicates that the user has exceeded the rate limits set by the 'Google Trends API'. For more information about the 'Google Trends API' - 'pytrends', visit <https://pypi.org/project/pytrends/>.

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2.70 score 3 scripts 133 downloads

wconf - Weighted Confusion Matrix

Allows users to create weighted confusion matrices and accuracy metrics that help with the model selection process for classification problems, where distance from the correct category is important. The package includes several weighting schemes which can be parameterized, as well as custom configuration options. Furthermore, users can decide whether they wish to positively or negatively affect the accuracy score as a result of applying weights to the confusion matrix. Functions are included to calculate accuracy metrics for imbalanced data. Finally, 'wconf' integrates well with the 'caret' package, but it can also work standalone when provided data in matrix form. References: Kuhn, M. (2008) "Building Perspective Models in R Using the caret Package" <doi:10.18637/jss.v028.i05> Monahov, A. (2021) "Model Evaluation with Weighted Threshold Optimization (and the mewto R package)" <doi:10.2139/ssrn.3805911> Monahov, A. (2024) "Improved Accuracy Metrics for Classification with Imbalanced Data and Where Distance from the Truth Matters, with the wconf R Package" <doi:10.2139/ssrn.4802336> Starovoitov, V., Golub, Y. (2020). New Function for Estimating Imbalanced Data Classification Results. Pattern Recognition and Image Analysis, 295–302 Van de Velden, M., Iodice D'Enza, A., Markos, A., Cavicchia, C. (2023) "A general framework for implementing distances for categorical variables" <doi:10.48550/arXiv.2301.02190>.

Detection of haplotype patterns that include single nucleotide polymorphisms (SNPs) and non-contiguous haplotypes that are associated with a phenotype. Methods for implementing HTRX are described in Yang Y, Lawson DJ (2023) <doi:10.1093/bioadv/vbad038> and Barrie W, Yang Y, Irving-Pease E.K, et al (2024) <doi:10.1038/s41586-023-06618-z>.

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2.70 score 6 scripts 206 downloads

lddmm - Longitudinal Drift-Diffusion Mixed Models (LDDMM)

Implementation of the drift-diffusion mixed model for category learning as described in Paulon et al. (2021) <doi:10.1080/01621459.2020.1801448>.

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openblascppopenmp

2.70 score 5 scripts 278 downloads

iperform - Time Series Performance

A tool to calculate the performance of a time series in a specific date or period. It is more intended for data analysis in the fields of finance, banking, telecommunications or operational marketing.

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2.70 score 137 downloads

Glarmadillo - Solve the Graphical Lasso Problem with 'Armadillo'

Efficiently implements the Graphical Lasso algorithm, utilizing the 'Armadillo' 'C++' library for rapid computation. This algorithm introduces an L1 penalty to derive sparse inverse covariance matrices from observations of multivariate normal distributions. Features include the generation of random and structured sparse covariance matrices, beneficial for simulations, statistical method testing, and educational purposes in graphical modeling. A unique function for regularization parameter selection based on predefined sparsity levels is also offered, catering to users with specific sparsity requirements in their models. The methodology for sparse inverse covariance estimation implemented in this package is based on the work of Friedman, Hastie, and Tibshirani (2008) <doi:10.1093/biostatistics/kxm045>.

rwarrior - R Warrior - An AI Programming Game

A port of Ruby Warrior. Teaches R programming in a fun and interactive way.

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2.70 score 1 stars 4 scripts 159 downloads

evalR - Evaluation of Unverified Code

The purpose of this package is to generate trees and validate unverified code. Trees are made by parsing a statement into a verification tree data structure. This will make it easy to port the statement into another language. Safe statement evaluations are done by executing the verification trees.

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cpp

2.70 score 1 scripts 147 downloads

rTCRBCRr - Repertoire Analysis of the Detected Clonotype

The 'TRUST4' or 'MiXCR' is used to identify the clonotypes. The goal of 'rTCRBCRr' is to process the results from these clonotyping tools, and analyze the clonotype repertoire metrics based on chain names and IGH isotypes. The manuscript is still under preparation for publication for now. The references describing the methods in this package will be added later.

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2.70 score 194 downloads

condGEE - Parameter Estimation in Conditional GEE for Recurrent Event Gap Times

Solves for the mean parameters, the variance parameter, and their asymptotic variance in a conditional GEE for recurrent event gap times, as described by Clement and Strawderman (2009) in the journal Biostatistics. Makes a parametric assumption for the length of the censored gap time.

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2.70 score 3 scripts 298 downloads

terminaldigits - Tests of Uniformity and Independence for Terminal Digits

Implements simulated tests for the hypothesis that terminal digits are uniformly distributed (chi-squared goodness-of-fit) and the hypothesis that terminal digits are independent from preceding digits (several tests of independence for r x c contingency tables). Also, for a number of distributions, implements Monte Carlo simulations for type I errors and power for the test of independence.

PubMedMining - Text-Mining of the 'PubMed' Repository

Easy function for text-mining the 'PubMed' repository based on defined sets of terms. The relationship between fix-terms (related to your research topic) and pub-terms (terms which pivot around your research focus) is calculated using the pointwise mutual information algorithm ('PMI'). Church, Kenneth Ward and Hanks, Patrick (1990) <https://www.aclweb.org/anthology/J90-1003/> A text file is generated with the 'PMI'-scores for each fix-term. Then for each collocation pairs (a fix-term + a pub-term), a text file is generated with related article titles and publishing years. Additional Author section will follow in the next version updates.

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2.70 score 3 scripts 195 downloads

miRNAss - Genome-Wide Discovery of Pre-miRNAs with few Labeled Examples

Machine learning method specifically designed for pre-miRNA prediction. It takes advantage of unlabeled sequences to improve the prediction rates even when there are just a few positive examples, when the negative examples are unreliable or are not good representatives of its class. Furthermore, the method can automatically search for negative examples if the user is unable to provide them. MiRNAss can find a good boundary to divide the pre-miRNAs from other groups of sequences; it automatically optimizes the threshold that defines the classes boundaries, and thus, it is robust to high class imbalance. Each step of the method is scalable and can handle large volumes of data.

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cppopenmp

2.70 score 1 stars 3 scripts 174 downloads

discoverableresearch - Checks Title, Abstract and Keywords to Optimise Discoverability

A suite of tools are provided here to support authors in making their research more discoverable. check_keywords() - this function checks the keywords to assess whether they are already represented in the title and abstract. check_fields() - this function compares terminology used across the title, abstract and keywords to assess where terminological diversity (i.e. the use of synonyms) could increase the likelihood of the record being identified in a search. The function looks for terms in the title and abstract that also exist in other fields and highlights these as needing attention. suggest_keywords() - this function takes a full text document and produces a list of unigrams, bigrams and trigrams (1-, 2- or 2-word phrases) present in the full text after removing stop words (words with a low utility in natural language processing) that do not occur in the title or abstract that may be suitable candidates for keywords. suggest_title() - this function takes a full text document and produces a list of the most frequently used unigrams, bigrams and trigrams after removing stop words that do not occur in the abstract or keywords that may be suitable candidates for title words. check_title() - this function carries out a number of sub tasks: 1) it compares the length (number of words) of the title with the mean length of titles in major bibliographic databases to assess whether the title is likely to be too short; 2) it assesses the proportion of stop words in the title to highlight titles with low utility in search engines that strip out stop words; 3) it compares the title with a given sample of record titles from an .ris import and calculates a similarity score based on phrase overlap. This highlights the level of uniqueness of the title. This version of the package also contains functions currently in a non-CRAN package called 'litsearchr' <https://github.com/elizagrames/litsearchr>.

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2.70 score 167 downloads

mosqcontrol - Mosquito Control Resource Optimization

This project aims to make an accessible model for mosquito control resource optimization. The model uses data provided by users to estimate the mosquito populations in the sampling area for the sampling time period, and the optimal time to apply a treatment or multiple treatments.

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2.70 score 5 scripts 64 downloads

SCOUTer - Simulate Controlled Outliers

Using principal component analysis as a base model, 'SCOUTer' offers a new approach to simulate outliers in a simple and precise way. The user can generate new observations defining them by a pair of well-known statistics: the Squared Prediction Error (SPE) and the Hotelling's T^2 (T^2) statistics. Just by introducing the target values of the SPE and T^2, 'SCOUTer' returns a new set of observations with the desired target properties. Authors: Alba González, Abel Folch-Fortuny, Francisco Arteaga and Alberto Ferrer (2020).

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2.70 score 2 scripts 174 downloads

binomialRF - Binomial Random Forest Feature Selection

The 'binomialRF' is a new feature selection technique for decision trees that aims at providing an alternative approach to identify significant feature subsets using binomial distributional assumptions (Rachid Zaim, S., et al. (2019)) <doi:10.1101/681973>. Treating each splitting variable selection as a set of exchangeable correlated Bernoulli trials, 'binomialRF' then tests whether a feature is selected more often than by random chance.

The Tweedie lasso model implements an iteratively reweighed least square (IRLS) strategy that incorporates a blockwise majorization decent (BMD) method, for efficiently computing solution paths of the (grouped) lasso and the (grouped) elastic net methods.

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openblasfortranglibc

2.66 score 3 stars 1 dependents 51 scripts 337 downloads

psre - Presenting Statistical Results Effectively

Includes functions and data used in the book "Presenting Statistical Results Effectively", Andersen and Armstrong (2022, ISBN: 978-1446269800). Several functions aid in data visualization - creating compact letter displays for simple slopes, kernel density estimates with normal density overlay. Other functions aid in post-model evaluation heatmap fit statistics for binary predictors, several variable importance measures, compact letter displays and simple-slope calculation. Finally, the package makes available the example datasets used in the book.

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2.66 score 151 scripts 248 downloads

triplediff - Triple-Difference Estimators

Implements triple-difference (DDD) estimators for both average treatment effects and event-study parameters. Methods include regression adjustment, inverse-probability weighting, and doubly-robust estimators, all of which rely on a conditional DDD parallel-trends assumption and allow covariate adjustment across multiple pre- and post-treatment periods. The methodology is detailed in Ortiz-Villavicencio and Sant'Anna (2025) <doi:10.48550/arXiv.2505.09942>.

whitening - Whitening and High-Dimensional Canonical Correlation Analysis

Implements the whitening methods (ZCA, PCA, Cholesky, ZCA-cor, and PCA-cor) discussed in Kessy, Lewin, and Strimmer (2018) "Optimal whitening and decorrelation", <doi:10.1080/00031305.2016.1277159>, as well as the whitening approach to canonical correlation analysis allowing negative canonical correlations described in Jendoubi and Strimmer (2019) "A whitening approach to probabilistic canonical correlation analysis for omics data integration", <doi:10.1186/s12859-018-2572-9>. The package also offers functions to simulate random orthogonal matrices, compute (correlation) loadings and explained variation. It also contains four example data sets (extended UCI wine data, TCGA LUSC data, nutrimouse data, extended pitprops data).

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2.63 score 2 dependents 71 scripts 752 downloads

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2.60 score 1 stars 40 scripts 231 downloads

InvariantCausalPrediction - Invariant Causal Prediction

Confidence intervals for causal effects, using data collected in different experimental or environmental conditions. Hidden variables can be included in the model with a more experimental version.

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2.60 score 4 stars 1 dependents 33 scripts 234 downloads

ManifoldOptim - An R Interface to the 'ROPTLIB' Library for Riemannian Manifold Optimization

An R interface to version 0.3 of the 'ROPTLIB' optimization library (see <https://www.math.fsu.edu/~whuang2/> for more information). Optimize real- valued functions over manifolds such as Stiefel, Grassmann, and Symmetric Positive Definite matrices. For details see Martin et. al. (2020) <doi:10.18637/jss.v093.i01>. Note that the optional ldr package used in some of this package's examples can be obtained from either JSS <https://www.jstatsoft.org/index.php/jss/article/view/v061i03/2886> or from the CRAN archives <https://cran.r-project.org/src/contrib/Archive/ldr/ldr_1.3.3.tar.gz>.

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openblascpp

2.60 score 3 dependents 44 scripts 414 downloads

wid - Download Data from the World Inequality Database

Tools to download data from the online World Inequality Database directly into R. The World Inequality Database is an extensive source on the historical evolution of the distribution of income and wealth both within and between countries. It relies on the combined effort of an international network of over a hundred researchers covering more than seventy countries from all continents.

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2.60 score 79 scripts 420 downloads

Reads European Data Format files EDF and EDF+, see <http://www.edfplus.info>, BioSemi Data Format files BDF, see <http://www.biosemi.com/faq/file_format.htm>, and BDF+ files, see <http://www.teuniz.net/edfbrowser/bdfplus%20format%20description.html>. The files are read in two steps: first the header is read and then the signals (using the header object as a parameter).

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2.59 score 35 scripts 1.1k downloads

tsBSS - Blind Source Separation and Supervised Dimension Reduction for Time Series

Different estimators are provided to solve the blind source separation problem for multivariate time series with stochastic volatility and supervised dimension reduction problem for multivariate time series. Different functions based on AMUSE and SOBI are also provided for estimating the dimension of the white noise subspace. The package is fully described in Nordhausen, Matilainen, Miettinen, Virta and Taskinen (2021) <doi:10.18637/jss.v098.i15>.

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openblascpp

2.58 score 4 stars 2 dependents 16 scripts 383 downloads

cmpp - Direct Parametric Inference for the Cumulative Incidence Function in Competing Risks

Implements parametric (Direct) regression methods for modeling cumulative incidence functions (CIFs) in the presence of competing risks. Methods include the direct Gompertz-based approach and generalized regression models as described in Jeong and Fine (2006) <doi:10.1111/j.1467-9876.2006.00532.x> and Jeong and Fine (2007) <doi:10.1093/biostatistics/kxj040>. The package facilitates maximum likelihood estimation, variance computation, with applications to clinical trials and survival analysis.

Routines for nonlinear time series analysis based on Threshold Autoregressive Moving Average (TARMA) models. It provides functions and methods for: TARMA model fitting and forecasting, including robust estimators, see Goracci et al. JBES (2025) <doi:10.1080/07350015.2024.2412011>; tests for threshold effects, see Giannerini et al. JoE (2024) <doi:10.1016/j.jeconom.2023.01.004>, Goracci et al. Statistica Sinica (2023) <doi:10.5705/ss.202021.0120>, Angelini et al. (2024) OBES <doi:10.1111/obes.12647>; unit-root tests based on TARMA models, see Chan et al. Statistica Sinica (2024) <doi:10.5705/ss.202022.0125>.

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openblasfortran

2.49 score 9 scripts 6.2k downloads

schoRsch - Tools for Analyzing Factorial Experiments

Offers a helping hand to psychologists and other behavioral scientists who routinely deal with experimental data from factorial experiments. It includes several functions to format output from other R functions according to the style guidelines of the APA (American Psychological Association). This formatted output can be copied directly into manuscripts to facilitate data reporting. These features are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious technician at the Department of Psychology III, University of Wuerzburg. For details on the implemented methods, see Roland Pfister and Markus Janczyk (2016) <doi: 10.20982/tqmp.12.2.p147>.

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2.49 score 2 stars 77 scripts 744 downloads

Modeling under- and over-dispersed count data using extended Poisson process models as in the article Faddy and Smith (2011) <doi:10.18637/jss.v069.i06> .

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2.48 score 30 scripts 260 downloads

cqrReg - Quantile, Composite Quantile Regression and Regularized Versions

Estimate quantile regression(QR) and composite quantile regression (cqr) and with adaptive lasso penalty using interior point (IP), majorize and minimize(MM), coordinate descent (CD), and alternating direction method of multipliers algorithms(ADMM).

2.45 score 3 dependents 31 scripts 382 downloads

CMLS - Constrained Multivariate Least Squares

Solves multivariate least squares (MLS) problems subject to constraints on the coefficients, e.g., non-negativity, orthogonality, equality, inequality, monotonicity, unimodality, smoothness, etc. Includes flexible functions for solving MLS problems subject to user-specified equality and/or inequality constraints, as well as a wrapper function that implements 24 common constraint options. Also does k-fold or generalized cross-validation to tune constraint options for MLS problems. See ten Berge (1993, ISBN:9789066950832) for an overview of MLS problems, and see Goldfarb and Idnani (1983) <doi:10.1007/BF02591962> for a discussion of the underlying quadratic programming algorithm.

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2.43 score 9 dependents 6 scripts 724 downloads

mpt - Multinomial Processing Tree Models

Fitting and testing multinomial processing tree (MPT) models, a class of nonlinear models for categorical data. The parameters are the link probabilities of a tree-like graph and represent the latent cognitive processing steps executed to arrive at observable response categories (Batchelder & Riefer, 1999 <doi:10.3758/bf03210812>; Erdfelder et al., 2009 <doi:10.1027/0044-3409.217.3.108>; Riefer & Batchelder, 1988 <doi:10.1037/0033-295x.95.3.318>).

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2.43 score 27 scripts 339 downloads

polyapost - Simulating from the Polya Posterior

Simulate via Markov chain Monte Carlo (hit-and-run algorithm) a Dirichlet distribution conditioned to satisfy a finite set of linear equality and inequality constraints (hence to lie in a convex polytope that is a subset of the unit simplex).

FRACTION - Numeric Number into Fraction

Turn numeric,data.frame,matrix into fraction form.

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2.40 score 2 dependents 21 scripts 289 downloads

smarter - A Collection of Modified R Functions to Make Basic Coding More Convenient

A collection of recycled and modified R functions to aid in file manipulation, data exploration, wrangling, optimization, and object manipulation. Other functions aid in convenient data visualization, loop progression, software packaging, and installation.

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cppopenmp

2.40 score 3 dependents 28 scripts 243 downloads

HDoutliers - Leland Wilkinson's Algorithm for Detecting Multidimensional Outliers

An implementation of an algorithm for outlier detection that can handle a) data with a mixed categorical and continuous variables, b) many columns of data, c) many rows of data, d) outliers that mask other outliers, and e) both unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, HDoutliers is based on a distributional model that uses probabilities to determine outliers.

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2.40 score 3 stars 1 dependents 28 scripts 459 downloads

mt.surv - Multi-Threshold Survival Analysis

Implements survival analyses across multiple abundance thresholds, repeatedly partitioning samples into groups and evaluating survival differences to assess taxonomic associations with outcomes.

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2.40 score 5 scripts 436 downloads

rCausalMGM - Scalable Causal Discovery and Model Selection on Mixed Datasets with 'rCausalMGM'

Scalable methods for learning causal graphical models from mixed data, including continuous, discrete, and censored variables. The package implements CausalMGM, which combines a convex, score-based approach for learning an initial moralized graph with a producer-consumer scheme that enables efficient parallel conditional independence testing in constraint-based causal discovery algorithms. The implementation supports high-dimensional datasets and provides individual access to core components of the workflow, including MGM and the PC-Stable and FCI-Stable causal discovery algorithms. To support practical applications, the package includes multiple model selection strategies, including information criteria based on likelihood and model complexity, cross-validation for out-of-sample likelihood estimation, and stability-based approaches that assess graph robustness across subsamples.

cpp

2.35 score 32 scripts 227 downloads

oceanmap - A Plotting Toolbox for 2D Oceanographic Data

Plotting toolbox for 2D oceanographic data (satellite data, sea surface temperature, chlorophyll, ocean fronts & bathymetry). Recognized classes and formats include netcdf, Raster, '.nc' and '.gz' files.

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2.35 score 1 stars 1 dependents 74 scripts 263 downloads

adimpro - Adaptive Smoothing of Digital Images

Implements tools for manipulation of digital images and the Propagation Separation approach by Polzehl and Spokoiny (2006) <DOI:10.1007/s00440-005-0464-1> for smoothing digital images, see Polzehl and Tabelow (2007) <DOI:10.18637/jss.v019.i01>.

A metric called 'Density-Based Clustering Validation index' (DBCV) index to evaluate clustering results, following the <https://github.com/pajaskowiak/clusterConfusion/blob/main/R/dbcv.R> 'R' implementation by Pablo Andretta Jaskowiak. Original 'DBCV' index article: Moulavi, D., Jaskowiak, P. A., Campello, R. J., Zimek, A., and Sander, J. (April 2014), "Density-based clustering validation", Proceedings of SDM 2014 -- the 2014 SIAM International Conference on Data Mining (pp. 839-847), <doi:10.1137/1.9781611973440.96>. A more recent article on the 'DBCV' index: Chicco, D., Sabino, G.; Oneto, L.; Jurman, G. (August 2025), "The DBCV index is more informative than DCSI, CDbw, and VIASCKDE indices for unsupervised clustering internal assessment of concave-shaped and density-based clusters", PeerJ Computer Science 11:e3095 (pp. 1-), <doi:10.7717/peerj-cs.3095>.

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2.30 score 8 scripts 513 downloads

CGNM - Cluster Gauss-Newton Method

Find multiple solutions of a nonlinear least squares problem. Cluster Gauss-Newton method does not assume uniqueness of the solution of the nonlinear least squares problem and compute multiple minimizers. Please cite the following paper when this software is used in your research: Aoki et al. (2020) <doi:10.1007/s11081-020-09571-2>. Cluster Gauss–Newton method. Optimization and Engineering, 1-31. Please cite the following paper when profile likelihood plot is drawn with this software and used in your research: Aoki and Sugiyama (2024) <doi:10.1002/psp4.13055>. Cluster Gauss-Newton method for a quick approximation of profile likelihood: With application to physiologically-based pharmacokinetic models. CPT Pharmacometrics Syst Pharmacol.13(1):54-67. GPT based helper bot available at <https://chatgpt.com/g/g-684936db9e748191a2796debb00cd755-cluster-gauss-newton-method-helper-bot>

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2.30 score 8 scripts 745 downloads

datetoiso - Convert and Impute Dates to ISO 8601 Format and Reconcile Data Sets

Provides tools for converting and imputing date values to the ISO 8601 standard format and for reconciling differences between two versions of a data set. The package automatically detects date patterns within data frame columns and converts them to consistent ISO-formatted dates, with optional imputation of missing day or month components based on user-defined rules. It also includes functionality to identify inserted, deleted, and updated records, as well as column- and value-level changes, when comparing old and new versions of a data frame. Only one date format may be applied within a single column.

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2.30 score 1 scripts 258 downloads

wdnr.gis - Pull Spatial Layers from 'WDNR ArcGIS REST API'

Functions for finding and pulling data from the 'Wisconsin Department of Natural Resources ArcGIS REST APIs' <https://dnrmaps.wi.gov/arcgis/rest/services> and <https://dnrmaps.wi.gov/arcgis2/rest/services>.

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2.30 score 1 stars 3 scripts 198 downloads

A collection of functions for testing randomness (or mutual independence) in linear and circular data as proposed in Gehlot and Laha (2025a) <doi:10.48550/arXiv.2506.21157> and Gehlot and Laha (2025b) <doi:10.48550/arXiv.2506.23522>, respectively.

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2.30 score 433 downloads

avseqmc - Anytime-Valid Sequential Estimation of Monte-Carlo p-Values

Anytime-valid sequential estimation of the p-value of a test calibrated by Monte-Carlo simulation, as described in Stoepker & Castro (2024) <doi:10.48550/arXiv.2409.18908>.

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2.30 score 5 scripts 155 downloads

integIRTy - Integrating Multiple Modalities of High Throughput Assays Using Item Response Theory

Provides a systematic framework for integrating multiple modalities of assays profiled on the same set of samples. The goal is to identify genes that are altered in cancer either marginally or consistently across different assays. The heterogeneity among different platforms and different samples are automatically adjusted so that the overall alteration magnitude can be accurately inferred. See Tong and Coombes (2012) <doi:10.1093/bioinformatics/bts561>.

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2.30 score 20 scripts 198 downloads

SIBERG - Systematic Identification of Bimodally Expressed Genes Using RNAseq Data

Provides models to identify bimodally expressed genes from RNAseq data based on the Bimodality Index. SIBERG models the RNAseq data in the finite mixture modeling framework and incorporates mechanisms for dealing with RNAseq normalization. Three types of mixture models are implemented, namely, the mixture of log normal, negative binomial, or generalized Poisson distribution. See Tong et al. (2013) <doi:10.1093/bioinformatics/bts713>.

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2.30 score 20 scripts 255 downloads

HDclust - Clustering High Dimensional Data with Hidden Markov Model on Variable Blocks

Clustering of high dimensional data with Hidden Markov Model on Variable Blocks (HMM-VB) fitted via Baum-Welch algorithm. Clustering is performed by the Modal Baum-Welch algorithm (MBW), which finds modes of the density function. Lin Lin and Jia Li (2017) <https://jmlr.org/papers/v18/16-342.html>.

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cppopenmp

2.30 score 20 scripts 237 downloads

prWarp - Warping Landmark Configurations

Compute bending energies, principal warps, partial warp scores, and the non-affine component of shape variation for 2D landmark configurations, as well as Mardia-Dryden distributions and self-similar distributions of landmarks, as described in Mitteroecker et al. (2020) <doi:10.1093/sysbio/syaa007>. Working examples to decompose shape variation into small-scale and large-scale components, and to decompose the total shape variation into outline and residual shape components are provided. Two landmark datasets are provided, that quantify skull morphology in humans and papionin primates, respectively from Mitteroecker et al. (2020) <doi:10.5061/dryad.j6q573n8s> and Grunstra et al. (2020) <doi:10.5061/dryad.zkh189373>.

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2.30 score 181 downloads

wwntests - Hypothesis Tests for Functional Time Series

Provides a collection of white noise hypothesis tests for functional time series and related visualizations. These include tests based on the norms of autocovariance operators that are built under both strong and weak white noise assumptions. Additionally, tests based on the spectral density operator and on principal component dimensional reduction are included, which are built under strong white noise assumptions. Also, this package provides goodness-of-fit tests for functional autoregressive of order 1 models. These methods are described in Kokoszka et al. (2017) <doi:10.1016/j.jmva.2017.08.004>, Characiejus and Rice (2019) <doi:10.1016/j.ecosta.2019.01.003>, Gabrys and Kokoszka (2007) <doi:10.1198/016214507000001111>, and Kim et al. (2023) <doi: 10.1214/23-SS143> respectively.

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2.30 score 2 stars 5 scripts 273 downloads

mvngGrAd - Moving Grid Adjustment in Plant Breeding Field Trials

Package for moving grid adjustment in plant breeding field trials.

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2.30 score 10 scripts 174 downloads

sparseDFM - Estimate Dynamic Factor Models with Sparse Loadings

Implementation of various estimation methods for dynamic factor models (DFMs) including principal components analysis (PCA) Stock and Watson (2002) <doi:10.1198/016214502388618960>, 2Stage Giannone et al. (2008) <doi:10.1016/j.jmoneco.2008.05.010>, expectation-maximisation (EM) Banbura and Modugno (2014) <doi:10.1002/jae.2306>, and the novel EM-sparse approach for sparse DFMs Mosley et al. (2023) <arXiv:2303.11892>. Options to use classic multivariate Kalman filter and smoother (KFS) equations from Shumway and Stoffer (1982) <doi:10.1111/j.1467-9892.1982.tb00349.x> or fast univariate KFS equations from Koopman and Durbin (2000) <doi:10.1111/1467-9892.00186>, and options for independent and identically distributed (IID) white noise or auto-regressive (AR(1)) idiosyncratic errors. Algorithms coded in 'C++' and linked to R via 'RcppArmadillo'.

Cluster user-supplied somatic read counts with corresponding allele-specific copy number and tumor purity to infer feasible underlying intra-tumor heterogeneity in terms of number of subclones, multiplicity, and allocation (Little et al. (2019) <doi:10.1186/s13073-019-0643-9>).

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openblascppopenmp

2.26 score 18 scripts 119 downloads

Simile - Interact with Simile Models

Allows a Simile model saved as a compiled binary to be loaded, parameterized, executed and interrogated. This version works with Simile v6 on.

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2.26 score 18 scripts 186 downloads

acc - Exploring Accelerometer Data

Processes accelerometer data from uni-axial and tri-axial devices, and generates data summaries. Also includes functions to plot, analyze, and simulate accelerometer data.

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openblascpp

2.26 score 1 stars 30 scripts 281 downloads

exploreR - Tools for Quickly Exploring Data

Simplifies some complicated and labor intensive processes involved in exploring and explaining data. Allows you to quickly and efficiently visualize the interaction between variables and simplifies the process of discovering covariation in your data. Also includes some convenience features designed to remove as much redundant typing as possible.

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2.26 score 18 scripts 182 downloads

DTWBI - Imputation of Time Series Based on Dynamic Time Warping

Functions to impute large gaps within time series based on Dynamic Time Warping methods. It contains all required functions to create large missing consecutive values within time series and to fill them, according to the paper Phan et al. (2017), <DOI:10.1016/j.patrec.2017.08.019>. Performance criteria are added to compare similarity between two signals (query and reference).

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2.24 score 1 dependents 58 scripts 460 downloads

insuranceData - A Collection of Insurance Datasets Useful in Risk Classification in Non-life Insurance.

Insurance datasets, which are often used in claims severity and claims frequency modelling. It helps testing new regression models in those problems, such as GLM, GLMM, HGLM, non-linear mixed models etc. Most of the data sets are applied in the project "Mixed models in ratemaking" supported by grant NN 111461540 from Polish National Science Center.

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2.24 score 1 stars 161 scripts 1.1k downloads

ACDm - Tools for Autoregressive Conditional Duration Models

Provides tools for autoregressive conditional duration (ACD, Engle and Russell, 1998) models. Functions to create trade, price, or volume durations from transaction data, perform diurnal adjustments, fit various ACD models, and test them.

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cpp

2.23 score 3 stars 1 dependents 19 scripts 430 downloads

Different evidential classifiers, which provide outputs in the form of Dempster-Shafer mass functions. The methods are: the evidential K-nearest neighbor rule, the evidential neural network, radial basis function neural networks, logistic regression, feed-forward neural networks.

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2.23 score 1 stars 17 scripts 272 downloads

GFD - Tests for General Factorial Designs

Implemented are the Wald-type statistic, a permuted version thereof as well as the ANOVA-type statistic for general factorial designs, even with non-normal error terms and/or heteroscedastic variances, for crossed designs with an arbitrary number of factors and nested designs with up to three factors. Friedrich et al. (2017) <doi:10.18637/jss.v079.c01>.

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2.23 score 17 scripts 257 downloads

shinyaframe - 'WebVR' Data Visualizations with 'RStudio Shiny' and 'Mozilla A-Frame'

Make R data available in Web-based virtual reality experiences for immersive, cross-platform data visualizations. Includes the 'gg-aframe' JavaScript package for a Grammar of Graphics declarative HTML syntax to create 3-dimensional data visualizations with 'Mozilla A-Frame' <https://aframe.io>.

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2.23 score 1 stars 17 scripts 169 downloads

mexhaz - Mixed Effect Excess Hazard Models

Fit flexible (excess) hazard regression models with the possibility of including non-proportional effects of covariables and of adding a random effect at the cluster level (corresponding to a shared frailty). A detailed description of the package functionalities is provided in Charvat and Belot (2021) <doi: 10.18637/jss.v098.i14>.

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2.23 score 1 dependents 28 scripts 387 downloads

EBEN - Empirical Bayesian Elastic Net

Provides the Empirical Bayesian Elastic Net for handling multicollinearity in generalized linear regression models. As a special case of the 'EBglmnet' package (also available on CRAN), this package encourages a grouping effects to select relevant variables and estimate the corresponding non-zero effects.

Investigating and visualising Bayesian Additive Regression Tree (BART) (Chipman, H. A., George, E. I., & McCulloch, R. E. 2010) <doi:10.1214/09-AOAS285> model fits. We construct conventional plots to analyze a model’s performance and stability as well as create new tree-based plots to analyze variable importance, interaction, and tree structure. We employ Value Suppressing Uncertainty Palettes (VSUP) to construct heatmaps that display variable importance and interactions jointly using colour scale to represent posterior uncertainty. Our visualisations are designed to work with the most popular BART R packages available, namely 'BART' Rodney Sparapani and Charles Spanbauer and Robert McCulloch 2021 <doi:10.18637/jss.v097.i01>, 'dbarts' (Vincent Dorie 2023) <https://CRAN.R-project.org/package=dbarts>, and 'bartMachine' (Adam Kapelner and Justin Bleich 2016) <doi:10.18637/jss.v070.i04>.

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openjdk

2.20 score 16 scripts 224 downloads

mwlaxeref - Cross-References Lake Identifiers Between Different Data Sets

Handy helper package for cross-referencing lake identifiers among different data sets in the Midwestern United States. There are multiple different state, regional, and federal agencies that have different identifiers on lakes. This package helps you to go between them.

Perform analysis of variance and other important complementary analyses. The functions are easy to use. Performs analysis in various designs, with balanced and unbalanced data.

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2.19 score 1 stars 72 scripts 1.1k downloads

twinning - Data Twinning

An efficient algorithm for data twinning. This work is supported by U.S. National Science Foundation grants DMREF-1921873 and CMMI-1921646.

Defines a graphics device and functions for graphical output in terminal emulators that support graphical output. Currently terminals that support the Terminal Graphics Protocol (<https://sw.kovidgoyal.net/kitty/graphics-protocol/>) and terminal supporting Sixel (<https://en.wikipedia.org/wiki/Sixel>) are supported.

SILGGM - Statistical Inference of Large-Scale Gaussian Graphical Model in Gene Networks

Provides a general framework to perform statistical inference of each gene pair and global inference of whole-scale gene pairs in gene networks using the well known Gaussian graphical model (GGM) in a time-efficient manner. We focus on the high-dimensional settings where p (the number of genes) is allowed to be far larger than n (the number of subjects). Four main approaches are supported in this package: (1) the bivariate nodewise scaled Lasso (Ren et al (2015) <doi:10.1214/14-AOS1286>) (2) the de-sparsified nodewise scaled Lasso (Jankova and van de Geer (2017) <doi:10.1007/s11749-016-0503-5>) (3) the de-sparsified graphical Lasso (Jankova and van de Geer (2015) <doi:10.1214/15-EJS1031>) (4) the GGM estimation with false discovery rate control (FDR) using scaled Lasso or Lasso (Liu (2013) <doi:10.1214/13-AOS1169>). Windows users should install 'Rtools' before the installation of this package.

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cpp

2.14 score 3 stars 23 scripts 257 downloads

mcanalysis - Markov Chain Analysis for Structural Behaviour and Stability

Analyses the stability and structural behaviour of export and import patterns across multiple countries using a Markov chain modelling framework. Constructs transition probability matrices to quantify changes in trade shares between successive periods, thereby capturing persistence, structural shifts, and inter-country interdependence in trade performance. By iteratively generating expected trade distributions over time, the approach facilitates assessment of stability, long-run equilibrium tendencies, and comparative dynamics in longitudinal trade data, providing a rigorous tool for empirical analysis of export–import behaviour. Methodological foundations follow standard Markov chain theory as described in Gagniuc (2017) <Doi:10.1002/9781119387596>.

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2.13 score 14k downloads

STB - Simultaneous Tolerance Bounds

Provides an implementation of simultaneous tolerance bounds (STB), useful for checking whether a numeric vector fits to a hypothetical null-distribution or not. Furthermore, there are functions for computing STB (bands, intervals) for random variates of linear mixed models fitted with package 'VCA'. All kinds of, possibly transformed (studentized, standardized, Pearson-type transformed) random variates (residuals, random effects), can be assessed employing STB-methodology.

smoothSurv - Survival Regression with Smoothed Error Distribution

Contains, as a main contribution, a function to fit a regression model with possibly right, left or interval censored observations and with the error distribution expressed as a mixture of G-splines. Core part of the computation is done in compiled 'C++' written using the 'Scythe' Statistical Library Version 0.3.

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cpp

2.10 score 2 dependents 21 scripts 498 downloads

relevent - Relational Event Models

Tools to fit and simulate realizations from relational event models.

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2.10 score 1 stars 1 dependents 42 scripts 725 downloads

BreakPoints - Identify Breakpoints in Series of Data

Compute Buishand Range Test, Pettit Test, SNHT, Student t-test, and Mann-Whitney Rank Test, to identify breakpoints in series. For all functions NA is allowed. Since all of the mention methods identify only one breakpoint in a series, a general function to look for N breakpoint is given. Also, the Yamamoto test for climate jump is available. Alexandersson, H. (1986) <doi:10.1002/joc.3370060607>, Buishand, T. (1982) <doi:10.1016/0022-1694(82)90066-X>, Hurtado, S. I., Zaninelli, P. G., & Agosta, E. A. (2020) <doi:10.1016/j.atmosres.2020.104955>, Mann, H. B., Whitney, D. R. (1947) <doi:10.1214/aoms/1177730491>, Pettitt, A. N. (1979) <doi:10.2307/2346729>, Ruxton, G. D., jul (2006) <doi:10.1093/beheco/ark016>, Yamamoto, R., Iwashima, T., Kazadi, S. N., & Hoshiai, M. (1985) <doi:10.2151/jmsj1965.63.6_1157>.

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2.10 score 2 dependents 21 scripts 233 downloads

bootComb - Combine Parameter Estimates via Parametric Bootstrap

Propagate uncertainty from several estimates when combining these estimates via a function. This is done by using the parametric bootstrap to simulate values from the distribution of each estimate to build up an empirical distribution of the combined parameter. Finally either the percentile method is used or the highest density interval is chosen to derive a confidence interval for the combined parameter with the desired coverage. Gaussian copulas are used for when parameters are assumed to be dependent / correlated. References: Davison and Hinkley (1997,ISBN:0-521-57471-4) for the parametric bootstrap and percentile method, Gelman et al. (2014,ISBN:978-1-4398-4095-5) for the highest density interval, Stockdale et al. (2020)<doi:10.1016/j.jhep.2020.04.008> for an example of combining conditional prevalences.

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2.10 score 25 scripts 245 downloads

RobKF - Innovative and/or Additive Outlier Robust Kalman Filtering

Implements a series of robust Kalman filtering approaches. It implements the additive outlier robust filters of Ruckdeschel et al. (2014) <arXiv:1204.3358> and Agamennoni et al. (2018) <doi:10.1109/ICRA.2011.5979605>, the innovative outlier robust filter of Ruckdeschel et al. (2014) <arXiv:1204.3358>, as well as the innovative and additive outlier robust filter of Fisch et al. (2020) <arXiv:2007.03238>.

smoothy - Automatic Estimation of the Most Likely Drug Combination using Smooth Algorithm

A flexible moving average algorithm for modeling drug exposure in pharmacoepidemiology studies as presented in the article: Ouchi, D., Giner-Soriano, M., Gómez-Lumbreras, A., Vedia Urgell, C.,Torres, F., & Morros, R. (2022). "Automatic Estimation of the Most Likely Drug Combination in Electronic Health Records Using the Smooth Algorithm : Development and Validation Study." JMIR medical informatics, 10(11), e37976. <doi:10.2196/37976>.

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2.08 score 12 scripts 152 downloads

EUfootball - Football Match Data of European Leagues

Contains match results from seven European men's football leagues, namely Premier League (England), Ligue 1 (France), Bundesliga (Germany), Serie A (Italy), Primera Division (Spain), Eredivisie (The Netherlands), Super Lig (Turkey). Includes Seasons 2010/2011 until 2019/2020 and a set of interesting covariates. Can be used all purposes.

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2.08 score 12 scripts 234 downloads

BSSprep - Whitening Data as Preparation for Blind Source Separation

Whitening is the first step of almost all blind source separation (BSS) methods. A fast implementation of whitening for BSS is implemented to serve as a lightweight dependency for packages providing BSS methods.

2.00 score 191 downloads

dcorBSS - Distance-Correlation Based Methods for Blind Source Separation and Dependence Analysis

Independent component analysis based on distance correlation, including a robust variant using the bowl transformation. The package provides user-facing implementations of distance covariance and distance correlation, including memory-efficient blockwise computations for large data sets. It includes a sequential ICA estimator based on minimizing distance correlation, as well as tools for analyzing serial dependence via distance autocorrelation, dependograms, and permutation-based tests. In addition, it provides functions for testing serial dependence based on distance correlation and the Hilbert–Schmidt independence criterion. The methodology is related to Matteson and Tsay (2017) <doi:10.1080/01621459.2016.1150851> and to the robust framework of Leyder et al. (2026) <doi:10.1007/s11634-026-00674-9>.

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cpp

2.00 score

NetSurvProx - 'NetSurvProx': Network-Based Survival Analysis via Proximal Methods

Introduces a novel network-constrained survival analysis framework for variable selection and parameter estimation in penalized survival models with convex penalties. The package extends two classical survival models, the Cox Proportional Hazards (PH) model and the Accelerated Failure Time (AFT) model, by incorporating prior biological knowledge from curated interaction networks (e.g., KEGG) into a double-penalty framework. The first penalty enforces variable selection through a LASSO penalty, while the second preserves gene-gene correlations by incorporating Laplacian-based constraints, ensuring that biologically relevant network structures are maintained. Using censored survival data, the method enables the identification of predictive biomarkers and pathways with potential relevance for target therapies. Model estimation is performed via proximal optimization algorithms combined with cross-validation for reliable tuning. To enhance interpretability, dedicated utility functions are implemented to consolidate results, yielding biologically coherent insights that can support personalized medicine and contribute to improved patient outcomes.

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2.00 score

treediff - Testing Differences Between Families of Trees

Perform test to detect differences in structure between families of trees. The method is based on cophenetic distances and aggregated Student's tests.

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2.00 score 147 downloads

NPFD - N-Power Fourier Deconvolution

Provides tools for non-parametric Fourier deconvolution using the N-Power Fourier Deconvolution (NPFD) method. This package includes methods for density estimation (densprf()) and sample generation (createSample()), enabling users to perform statistical analyses on mixed or replicated data sets.

Provides simple and powerful interfaces that facilitate interaction with 'ODBC' data sources. Each data source gets its own unique and dedicated interface, wrapped around 'RODBC'. Communication settings are remembered between queries, and are managed silently in the background. The interfaces support multi-statement 'SQL' scripts, which can be parameterised via metaprogramming structures and embedded 'R' expressions.

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2.00 score 10 scripts 637 downloads

MFSD - Multivariate Functional Spatial Data

Analysis of multivariate functional spatial data, including spectral multivariate functional principal component analysis and related statistical procedures (Si-Ahmed, Idris, et al. "Principal component analysis of multivariate spatial functional data." Big Data Research 39 (2025) 100504). (Kuenzer, T., Hörmann, S., & Kokoszka, P. (2021). "Principal component analysis of spatially indexed functions." Journal of the American Statistical Association, 116(535), 1444-1456.) (Happ, C., & Greven, S. (2018). "Multivariate functional principal component analysis for data observed on different (dimensional) domains." Journal of the American Statistical Association, 113(522), 649-659.)

Simulation and estimation for Neyman-Scott spatial cluster point process models and their extensions, based on the methodology in Tanaka, Ogata, and Stoyan (2008) <doi:10.1002/bimj.200610339>. To estimate parameters by the simplex method, parallel computation using 'OpenMP' application programming interface is available. For more details see Tanaka, Saga and Nakano <doi:10.18637/jss.v098.i06>.

Priority-ElasticNet extends the Priority-LASSO method (Klau et al. (2018) <doi:10.1186/s12859-018-2344-6>) by incorporating the ElasticNet penalty, allowing for both L1 and L2 regularization. This approach fits successive ElasticNet models for several blocks of (omics) data with different priorities, using the predicted values from each block as an offset for the subsequent block. It also offers robust options to handle block-wise missingness in multi-omics data, improving the flexibility and applicability of the model in the presence of incomplete datasets.

Implements likelihood-based evidence ratios for unified reporting in classical statistical testing. The package reports effect estimates, uncertainty intervals, and likelihood ratios on the log 10 scale derived from a single statistical model. It applies to standard normal mean tests, contingency tables, and regression coefficients, and provides a direct evidential measure while retaining classical error guarantees. For the Evidence Ratio Reporting Standard see Lawless (2026) <doi:10.5281/zenodo.18261076>.

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2.00 score 4 scripts 134 downloads

pwlmm - PWIGLS for Two-Level Multivariate and Multilevel Linear Models

Estimates two-level multilevel linear model and two-level multivariate linear multilevel model with weights following Probability Weighted Iterative Generalised Least Squares approach. For details see Veiga et al.(2014) <doi:10.1111/rssc.12020>.

Provides functions for implementing the Generalized Bayesian Optimal Phase II (G-BOP2) design using various Particle Swarm Optimization (PSO) algorithms, including: - PSO-Default, based on Kennedy and Eberhart (1995) <doi:10.1109/ICNN.1995.488968>, "Particle Swarm Optimization"; - PSO-Quantum, based on Sun, Xu, and Feng (2004) <doi:10.1109/ICCIS.2004.1460396>, "A Global Search Strategy of Quantum-Behaved Particle Swarm Optimization"; - PSO-Dexp, based on Stehlík et al. (2024) <doi:10.1016/j.asoc.2024.111913>, "A Double Exponential Particle Swarm Optimization with Non-Uniform Variates as Stochastic Tuning and Guaranteed Convergence to a Global Optimum with Sample Applications to Finding Optimal Exact Designs in Biostatistics"; - and PSO-GO.

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cpp

2.00 score 1 stars 209 downloads

quantbayes - Bayesian Quantification of Evidence Sufficiency

Implements the Quantification Evidence Standard algorithm for computing Bayesian evidence sufficiency from binary evidence matrices. It provides posterior estimates, credible intervals, percentiles, and optional visual summaries. The method is universal, reproducible, and independent of any specific clinical or rule based framework. For details see The Quantitative Omics Epidemiology Group et al. (2025) <doi:10.64898/2025.12.02.25341503>.

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2.00 score 8 scripts 162 downloads

Generate decision tables and simulate operating characteristics for phase I dose-finding designs to enable objective comparison across methods. Supported designs include the traditional 3+3, Bayesian Optimal Interval (BOIN) (Liu and Yuan (2015) <doi:10.1158/1078-0432.CCR-14-1526>), modified Toxicity Probability Interval-2 (mTPI-2) (Guo et al. (2017) <doi:10.1002/sim.7185>), interval 3+3 (i3+3) (Liu et al. (2020) <doi:10.1177/0962280220939123>), and Generalized 3+3 (G3). Provides visualization tools for comparing decision rules and operating characteristics across multiple designs simultaneously.

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2.00 score 184 downloads

geneExpressionFromGEO - Easily Downloads a Gene Expression Dataset from a GEO Code and Retrieves the Gene Symbols of Its Probesets

A function that reads in the GEO code of a gene expression dataset, retrieves its data from GEO, (optionally) retrieves the gene symbols of the dataset, and returns a simple dataframe table containing all the data. Platforms available: GPL11532, GPL23126, GPL6244, GPL8300, GPL80, GPL96, GPL570, GPL571, GPL20115, GPL1293, GPL6102, GPL6104, GPL6883, GPL6884, GPL13497, GPL14550, GPL17077, GPL6480. GEO: Gene Expression Omnibus. ID: identifier code. The GEO datasets are downloaded from the URL <https://ftp.ncbi.nlm.nih.gov/geo/series/>. More information can be found in the following manuscript: Davide Chicco, "geneExpressionFromGEO: an R package to facilitate data reading from Gene Expression Omnibus (GEO)". Microarray Data Analysis, Methods in Molecular Biology, volume 2401, chapter 12, pages 187-194, Springer Protocols, 2021, <doi:10.1007/978-1-0716-1839-4_12>.

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2.00 score 8 scripts 270 downloads

nmaplateplot - The Plate Plot for Network Meta-Analysis Results

A graphical display of results from network meta-analysis (NMA). It is suitable for outcomes like odds ratio (OR), risk ratio (RR), risk difference (RD) and standardized mean difference (SMD). It also has an option to visually display and compare the surface under the cumulative ranking (SUCRA) of different treatments.

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2.00 score 1 stars 4 scripts 182 downloads

statisR - STATIS and STATIS DUAL Multivariate Methods

Provides tools for the integration and exploration of data tables measured on the same set of observational units. The package includes methods to assess similarities among tables, extract common patterns across variable blocks, and create visual summaries that highlight shared structures in multiblock data.

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2.00 score 137 downloads

trunmnt - Moments of Truncated Multivariate Normal Distribution

Computes the product moments of the truncated multivariate normal distribution, particularly for cases involving patterned variance-covariance matrices. It also has the capability to calculate these moments with arbitrary positive-definite matrices, although performance may degrade for high-dimensional variables.

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openblascpp

2.00 score 114 downloads

TopicTestlet - A Topic Testlet Model for Calibrating Testlet Constructed Responses

Implements the Topic Testlet Model (TTM) as described by Xiong et al. (2025) <doi:10.1111/jedm.70001>. The package integrates Latent Dirichlet Allocation (LDA) with the Partial Credit Model to account for local item dependence in testlets using latent topics from student textual responses.

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2.00 score 107 downloads

Implements a simple, novel clustering algorithm based on optimizing the silhouette width. See <doi:10.1101/2023.11.07.566055> for details.

The empirical cumulative average deviation function introduced by the author is utilized to develop both Ad- and Ud-plots. The Ad-plot can identify symmetry, skewness, and outliers of the data distribution, including anomalies. The Ud-plot created by slightly modifying Ad-plot is exceptional in assessing normality, outperforming normal QQ-plot, normal PP-plot, and their derivations. The d-value that quantifies the degree of proximity between the Ud-plot and the graph of the estimated normal density function helps guide to make decisions on confirmation of normality. Full description of this methodology can be found in the article by Wijesuriya (2025) <doi:10.1080/03610926.2024.2440583>.

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2.00 score 167 downloads

sts - Estimation of the Structural Topic and Sentiment-Discourse Model for Text Analysis

The Structural Topic and Sentiment-Discourse (STS) model allows researchers to estimate topic models with document-level metadata that determines both topic prevalence and sentiment-discourse. The sentiment-discourse is modeled as a document-level latent variable for each topic that modulates the word frequency within a topic. These latent topic sentiment-discourse variables are controlled by the document-level metadata. The STS model can be useful for regression analysis with text data in addition to topic modeling’s traditional use of descriptive analysis. The method was developed in Chen and Mankad (2024) <doi:10.1287/mnsc.2022.00261>.

Perform two linear combination methods for biomarkers: (1) Empirical performance optimization for specificity (or sensitivity) at a controlled sensitivity (or specificity) level of Huang and Sanda (2022) <doi:10.1214/22-aos2210>, and (2) weighted maximum score estimator with empirical minimization of averaged false positive rate and false negative rate. Both adopt the algorithms of Huang and Sanda (2022) <doi:10.1214/22-aos2210>. 'MOSEK' solver is used and needs to be installed; an academic license for 'MOSEK' is free.

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2.00 score 3 scripts 263 downloads

PerMat - Performance Metrics in Predictive Modeling

Performance metric provides different performance measures like mean squared error, root mean square error, mean absolute deviation, mean absolute percentage error etc. of a fitted model. These can provide a way for forecasters to quantitatively compare the performance of competing models. For method details see (i) Pankaj Das (2020) <http://krishi.icar.gov.in/jspui/handle/123456789/44138>.

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2.00 score 1 scripts 527 downloads

Analyzes raw abundance data from a cellular thermal shift experiment and calculates melt temperatures and melt shifts for each protein in the experiment. McCracken (2022) <doi:10.1101/2022.12.30.522131>.

Implementation in a simple and efficient way of fully customisable population genetics simulations, considering multiple loci that have epistatic interactions. Specifically suited to the modelling of multilocus nucleocytoplasmic systems (with both diploid and haploid loci), it is nevertheless possible to simulate purely diploid (or purely haploid) genetic models. Examples of models that can be simulated with Ease are numerous, for example models of genetic incompatibilities as presented by Marie-Orleach et al. (2022) <doi:10.1101/2022.07.25.501356>. Many others are conceivable, although few are actually explored, Ease having been developed in particular to provide a solution so that these kinds of models can be simulated simply.

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cpp

2.00 score 5 scripts 173 downloads

MultiGlarmaVarSel - Variable Selection in Sparse Multivariate GLARMA Models

Performs variable selection in high-dimensional sparse GLARMA models. For further details we refer the reader to the paper Gomtsyan et al. (2022), <arXiv:2208.14721>.

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2.00 score 1 stars 3 scripts 190 downloads

NHSDataDictionaRy - NHS Data Dictionary Toolset for NHS Lookups

Providing a common set of simplified web scraping tools for working with the NHS Data Dictionary <https://datadictionary.nhs.uk/data_elements_overview.html>. The intended usage is to access the data elements section of the NHS Data Dictionary to access key lookups. The benefits of having it in this package are that the lookups are the live lookups on the website and will not need to be maintained. This package was commissioned by the NHS-R community <https://nhsrcommunity.com/> to provide this consistency of lookups. The OpenSafely lookups have now been added <https://www.opencodelists.org/docs/>.

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2.00 score 6 scripts 219 downloads

IIVpredictor - Modeling Within Individual Variability as Predictor

Time parceling method and Bayesian variability modeling methods for modeling within individual variability indicators as predictors.For more details, see <https://github.com/xliu12/IIVpredicitor>.

Algorithms for classical symmetric and deflation-based FastICA, reloaded deflation-based FastICA algorithm and an algorithm for adaptive deflation-based FastICA using multiple nonlinearities. For details, see Miettinen et al. (2014) <doi:10.1109/TSP.2014.2356442> and Miettinen et al. (2017) <doi:10.1016/j.sigpro.2016.08.028>. The package is described in Miettinen, Nordhausen and Taskinen (2018) <doi:10.32614/RJ-2018-046>.

By gaining the property of emergence through self-organization, the enhancement of SOMs(self organizing maps) is called Emergent SOM (ESOM). The result of the projection by ESOM is a grid of neurons which can be visualised as a three dimensional landscape in form of the Umatrix. Further details can be found in the referenced publications (see url). This package offers tools for calculating and visualising the ESOM as well as Umatrix, Pmatrix and UStarMatrix. All the functionality is also available through graphical user interfaces implemented in 'shiny'. Based on the recognized data structures, the method can be used to generate new data.

Detects multiple changes in slope using the CPOP dynamic programming approach of Fearnhead, Maidstone, and Letchford (2019) <doi:10.1080/10618600.2018.1512868>. This method finds the best continuous piecewise linear fit to data under a criterion that measures fit to data using the residual sum of squares, but penalizes complexity based on an L0 penalty on changes in slope. Further information regarding the use of this package with detailed examples can be found in Fearnhead and Grose (2024) <doi:10.18637/jss.v109.i07>.

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cpp

1.86 score 36 scripts 224 downloads

IPEC - Root Mean Square Curvature Calculation

Calculates the RMS intrinsic and parameter-effects curvatures of a nonlinear regression model. The curvatures are global measures of assessing whether a model/data set combination is close-to-linear or not. See Bates and Watts (1980) <doi:10.1002/9780470316757> and Ratkowsky and Reddy (2017) <doi:10.1093/aesa/saw098> for details.

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1.86 score 12 scripts 253 downloads

lmf - Functions for Estimation and Inference of Selection in Age-Structured Populations

Provides methods for estimation and statistical inference on directional and fluctuating selection in age-structured populations.

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1.86 score 1 dependents 24 scripts 212 downloads

HUM - Compute HUM Value and Visualize ROC Curves

Tools for computing HUM (Hypervolume Under the Manifold) value to estimate features ability to discriminate the class labels, visualizing the ROC curve for two or three class labels (Natalia Novoselova, Cristina Della Beffa, Junxi Wang, Jialiang Li, Frank Pessler, Frank Klawonn (2014) <doi:10.1093/bioinformatics/btu086>).

biostats101 - Practical Functions for Biostatistics Beginners

A set of user-friendly functions designed to fill gaps in existing introductory biostatistics R tools, making it easier for newcomers to perform basic biostatistical analyses without needing advanced programming skills. The methods implemented in this package are based on the works: Connor (1987) <doi:10.2307/2531961> Fleiss, Levin, & Paik (2013, ISBN:978-1-118-62561-3) Levin & Chen (1999) <doi:10.1080/00031305.1999.10474431> McNemar (1947) <doi:10.1007/BF02295996>.

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1.81 score 13 scripts 187 downloads

mpower - Power Analysis via Monte Carlo Simulation for Correlated Data

A flexible framework for power analysis using Monte Carlo simulation for settings in which considerations of the correlations between predictors are important. Users can set up a data generative model that preserves dependence structures among predictors given existing data (continuous, binary, or ordinal). Users can also generate power curves to assess the trade-offs between sample size, effect size, and power of a design. This package includes several statistical models common in environmental mixtures studies. For more details and tutorials, see Nguyen et al. (2022) <arXiv:2209.08036>.

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1.81 score 1 stars 13 scripts 289 downloads

fastmit - Fast Mutual Information Based Independence Test

A mutual information estimator based on k-nearest neighbor method proposed by A. Kraskov, et al. (2004) <doi:10.1103/PhysRevE.69.066138> to measure general dependence and the time complexity for our estimator is only squared to the sample size, which is faster than other statistics. Besides, an implementation of mutual information based independence test is provided for analyzing multivariate data in Euclidean space (T B. Berrett, et al. (2019) <doi:10.1093/biomet/asz024>); furthermore, we extend it to tackle datasets in metric spaces.

cpp

1.78 score 2 stars 1 dependents 9 scripts 391 downloads

ChernoffDist - Chernoff's Distribution

Computes Chernoff's distribution based on the method in Piet Groeneboom & Jon A Wellner (2001) Computing Chernoff's Distribution, Journal of Computational and Graphical Statistics, 10:2, 388-400, <doi:10.1198/10618600152627997>. Chernoff's distribution is defined as the distribution of the maximizer of the two-sided Brownian motion minus quadratic drift. That is, Z = argmax (B(t)-t^2).

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1.78 score 2 dependents 2 scripts 209 downloads

CPE - Concordance Probability Estimates in Survival Analysis

Concordance probability estimate (CPE) is a commonly used performance measure in survival analysis that evaluates the predictive accuracy of a survival model. It measures how well a model can distinguish between pairs of individuals with different survival times. Specifically, it calculate the proportion of all pairs of individuals whose predicted survival times are correctly ordered.

seasonalytics - Compute Seasonality Index, Seasonalized and Deseaonalised the Time Series Data

The computation of a seasonal index is a fundamental step in time-series forecasting when the data exhibits seasonality. Specifically, a seasonal index quantifies — for each season (e.g. month, quarter, week) — the relative magnitude of the seasonal effect compared to the overall average level of the series. This package has been developed to compute seasonal index for time series data and it also seasonalise and desesaonalise the time series data.

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1.76 score 5.8k downloads

factorplot - Presenting Pairwise Comparisons

The tools herein calculate, print, summarize and plot pairwise differences that result from generalized linear models, general linear hypothesis tests and multinomial logistic regression models. For more information, see Armstrong (2013) <doi:10.32614/RJ-2013-021>.

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1.76 score 29 scripts 204 downloads

onlinePCA - Online Principal Component Analysis

Online PCA for multivariate and functional data using perturbation methods, low-rank incremental methods, and stochastic optimization methods.

mpr - Multi-Parameter Regression (MPR)

Fitting Multi-Parameter Regression (MPR) models to right-censored survival data. These are flexible parametric regression models which extend standard models, for example, proportional hazards. See Burke & MacKenzie (2016) <doi:10.1111/biom.12625> and Burke et al (2020) <doi:10.1111/rssc.12398>.

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1.75 score 56 scripts 970 downloads

twl - Two-Way Latent Structure Clustering Model

Implementation of a Bayesian two-way latent structure model for integrative genomic clustering. The model clusters samples in relation to distinct data sources, with each subject-dataset receiving a latent cluster label, though cluster labels have across-dataset meaning because of the model formulation. A common scaling across data sources is unneeded, and inference is obtained by a Gibbs Sampler. The model can fit multivariate Gaussian distributed clusters or a heavier-tailed modification of a Gaussian density. Uniquely among integrative clustering models, the formulation makes no nestedness assumptions of samples across data sources -- the user can still fit the model if a study subject only has information from one data source. The package provides a variety of post-processing functions for model examination including ones for quantifying observed alignment of clusterings across genomic data sources. Run time is optimized so that analyses of datasets on the order of thousands of features on fewer than 5 datasets and hundreds of subjects can converge in 1 or 2 days on a single CPU. See "Swanson DM, Lien T, Bergholtz H, Sorlie T, Frigessi A, Investigating Coordinated Architectures Across Clusters in Integrative Studies: a Bayesian Two-Way Latent Structure Model, 2018, <doi:10.1101/387076>, Cold Spring Harbor Laboratory" at <https://www.biorxiv.org/content/early/2018/08/07/387076.full.pdf> for model details.

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1.75 score 56 scripts 241 downloads

R on FHIR is an easy to use wrapper around the 'HL7 FHIR' REST API (STU 3 and R4). It provides tools to easily read and search resources on a FHIR server and brings the results into the R environment. R on FHIR is based on the FhirClient of the official 'HL7 FHIR .NET API', also made by Firely.

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1.74 score 11 scripts 62 downloads

Provides estimation and covariate selection tools for Emax regression models using nonlinear least squares methods. Supported optimization algorithms are Gauss-Newton, Levenberg-Marquardt, and the port library for bounded optimization. The package also provides tools to assist in simulation work using Emax regression.

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1.70 score 3 scripts

droughtevents - Identify and Characterize Drought Events from Drought Index Time Series

Detects, describes, and analyzes drought events from time series of drought indices, such as the Standardized Precipitation-Evapotranspiration Index (SPEI). Identifies drought episodes based on threshold values and calculates their duration, intensity, severity, and peak month. Includes utilities for summarizing and visualizing drought dynamics over time. The Standardized Precipitation-Evapotranspiration Index is described in Vicente-Serrano et al. (2010) <doi:10.1175/2009JCLI2909.1>.

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1.70 score 3 scripts

icarm - Interpretable Contextual-Accountable and Responsible Machine Learning

A general-purpose framework for Interpretable Contextual-Accountable and Responsible Machine Learning (ICARM) that works with any clean tabular data across any application domain including healthcare, finance, social science, business, and education. Automatically detects whether a prediction task is binary classification, multi-class classification, or regression from the target variable type. Provides a unified entry point icarm_fit() supporting both interpretable learners (Classification and Regression Trees (CART), logistic regression, linear regression, Generalized Additive Models (GAM)) and extended learners (random forest, 'XGBoost', Support Vector Machines (SVM)) with consistent interfaces for global and local model explanation, group-level fairness auditing across protected attributes, probability calibration, threshold analysis, multi-model comparison, reproducible JavaScript Object Notation (JSON) audit trails, and accountability scorecards. The contextual accountability framing emphasises that algorithmic fairness and interpretability requirements depend on the deployment domain and must be evaluated accordingly. Extends the 'civic.icarm' framework (Awe 2025) <https://cran.r-project.org/package=civic.icarm> to general-purpose applications beyond civic and political education.

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1.70 score

porter - Generate Port Files for C Libraries

Generate port files for foreign function interfaces to C libraries by parsing C-family header files with 'CastXML'.

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1.70 score 5 scripts

sceua - Shuffled Complex Evolution Algorithm for Optimization

Provides an 'R' interface to a 'Rust' implementation of the Shuffled Complex Evolution - University of Arizona (SCE-UA) global optimization algorithm (Duan et al., 1992). SCE-UA combines simplex search, competitive evolution, and complex shuffling to solve nonlinear, non-convex, continuous parameter estimation problems. The method is commonly used for calibrating hydrological and environmental models and follows the algorithm proposed by Duan et al. (1992) <doi:10.1029/91WR02985>.

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rustcargo

1.70 score 4 scripts

DataCraftR - Create Datasets Interactively Using 'shiny'

Set of 'shiny'-based 'RStudio' add-ins for interactively creating datasets through graphical interfaces. Users can adjust graphical elements to define data generation parameters, and the resulting datasets can be saved to temporary RDS files for further analysis or visualization. Methods are described in: Chang et al. (2024) <https://CRAN.R-project.org/package=shiny>; Bostock et al. (2011) <doi:10.1109/TVCG.2011.185>.

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1.70 score 1 scripts

ggalttext - Make 'ggplot2' Fully Accessible by Generating Alternative Text

Generates concise alternative text for data visualizations created with 'ggplot2'. Descriptions are produced by inspecting plot layers, labels, scales, and facets, with support for multiple languages and alternative text stored in plot metadata.

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1.70 score 2 scripts

ggbond - Interactive Layout Editor for 'R' Plots

Provides a 'shiny'-based layout editor for arranging 'R' plot objects on a fixed-size canvas. It supports 'ggplot2' plots, 'graphics' functions and recorded plots, 'pheatmap' objects, 'ComplexHeatmap' objects, 'grid' grobs, 'gtable' objects, and local raster images, with live preview and PDF or PNG export.

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1.70 score

A bootstrapper that launches a command-line coding agent of the user's choice in a terminal tab pre-configured for a professional R role. Each role is described by a curated harness: a subset of community skills, a system prompt, a folder layout, and quality gates. The package does not run an agent loop and does not call a language model; it discovers the chosen coder binary, generates its configuration, links the curated skills, and opens the terminal. Code written by the agent is run manually by the user, by design, so that every generated script passes through a human audit gate before execution.

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1.70 score 1 scripts

rrstools - Analyzing RoboCupRescue Simulation Data

Tools for analyzing data from RoboCupRescue Simulation (RRS) <https://rescuesim.robocup.org>, a disaster rescue simulation platform. Supports reading virtual city map and disaster scenario files into analyzable data structures and provides functions for their visualization.

schmear - Build Structured Data Frame Subtypes

Provides developer-focused helper functions and S3 classes to ease the creation of structured subtypes of data frames. Developers can require certain columns and types to be present, and can enforce crossing and nesting relationships between values in different columns. Type-specific metadata and attributes are preserved through common data frame manipulations.

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1.70 score

potentiomap - Build Potentiometric Surfaces and Flow Arrows

Builds potentiometric surface products from groundwater monitoring data. The package prepares groundwater observations from direct water-level measurements or depth-to-water data paired with land-surface elevations, interpolates thin-plate spline surfaces by default, supports alternative and user-supplied interpolation methods, exports raster and contour products, and derives hydraulic-gradient flow arrows. Raster operations use methods from Hijmans (2025) <doi:10.32614/CRAN.package.terra>, thin-plate spline interpolation uses methods from Nychka et al. (2021) <doi:10.5065/D6W957CT>, and geostatistical interpolation uses methods from Pebesma (2004) <doi:10.1016/j.cageo.2004.03.012>.

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1.70 score

SimuRg - Building, Fitting and Evaluating PK/PD Modeles

Provides a unified workflow for building, fitting using external engines, and evaluating ordinary differential equation (ODE)-based pharmacokinetic/pharmacodynamic (PK/PD) models. Supports generation of estimation scenarios and control files for external engines (e.g., 'Monolix'), simulation of models using 'rxode2', and creation of goodness-of-fit diagnostics. Includes tools for covariate modeling, virtual population design, and local and global sensitivity analyses.

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1.70 score 5 scripts 417 downloads

SISIR - Select Intervals Suited for Functional Regression

Interval fusion and selection procedures for regression with functional inputs. Methods include a semiparametric approach based on Sliced Inverse Regression (SIR), as described in <doi:10.1007/s11222-018-9806-6> (standard ridge and sparse SIR are also included in the package) and a random forest based approach, as described in <doi:10.1002/sam.11705>.

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1.70 score 8 scripts 558 downloads

Implementations of Power Fuzzy Clustering (PFC) and Power Fuzzy Cluster-wise Regression (PFCR) for multivariate data. The package supports Minkowski distances, with the L1 case solved via iteratively re-weighted least squares and the case p > 1 solved via coordinate-wise root finding, as well as an adaptive, regularised Mahalanobis distance with per-cluster covariance matrices. Both plain fuzzy clustering and cluster-wise linear regression are provided. The corresponding paper can be found at Nguyen P.T., Tortora C., and Punzo A. (2026) <doi:10.1109/TFUZZ.2026.3683998>.

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1.70 score 359 downloads

Non-Uniform Fast Fourier Transform ('NUFFT')-accelerated local polynomial regression and kernel density estimation for large, scattered, or complex-valued datasets. Provides automatic bandwidth selection via Generalized Cross-Validation (GCV) for regression and Likelihood Cross-Validation (LCV) for density estimation. This is the 'R' port of the 'fastLPR' 'MATLAB'/'Python' toolbox, achieving O(N + M log M) computational complexity through custom 'NUFFT' implementation with Gaussian gridding. Supports 1D/2D/3D data, complex-valued responses, heteroscedastic variance estimation, and confidence interval computation. Performance optimized with vectorized 'R' code and compiled helpers via 'Rcpp'/'RcppArmadillo'. Extends the 'FKreg' toolbox of Wang et al. (2022) <doi:10.48550/arXiv.2204.07716> with 'Python' and 'R' ports. Applied in Li et al. (2022) <doi:10.1016/j.neuroimage.2022.119190>. Uses 'NUFFT' methods based on Greengard and Lee (2004) <doi:10.1137/S003614450343200X>, binning-accelerated kernel estimation of Wand (1994) <doi:10.1080/10618600.1994.10474656>, and local polynomial regression framework of Fan and Gijbels (1996, ISBN:978-0412983214).

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fftw3cppopenmp

1.70 score 462 downloads

emBALVI - EM Bayesian Adaptive LASSO Variational Inference Based GWAS

Performs Genome-Wide Association Study (GWAS) analysis using Expectation-Maximization Bayesian Adaptive LASSO with Variational Inference (emBALVI). Includes genotype preprocessing, genomic relationship matrix construction, GWAS analysis, Manhattan and QQ plotting.s.

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1.70 score 399 downloads

CompositionalSR - Spatial Regression Models with Compositional Data

Spatial and non-spatial regression models with compositional responses (and compositional predictors) using the alpha--transformation. Relevant papers include: Tsagris M. and Pantazis Y. (2026), <doi:10.48550/arXiv.2510.12663>, Tsagris M. (2015), <https://soche.cl/chjs/volumes/06/02/Tsagris(2015).pdf>, Tsagris M.T., Preston S. and Wood A.T.A. (2011), <doi:10.48550/arXiv.1106.1451>.

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1.70 score 492 downloads

uuidx - Modern UUIDs for R with a Rust Backend

Generate, parse, and validate RFC 9562 UUIDs from R using the Rust 'uuid' crate via 'extendr'. Developed by Thomas Bryce Kelly at Icy Seas Co-Laboratory LLC. Version 7 UUIDs are the default for new identifiers, while versions 4, 5, 6, and legacy version 1 are also supported. Functions return character vectors by default and can also expose 16-byte raw representations for low-level workflows.

1.70 score 1 scripts 526 downloads

remode - Recursive Mode Detection for Distributions of Ordinal Data

Provides the function remode() for recursive modality detection in ordinal data. 'remode' is an algorithm specifically designed to estimate the number and location of modes in ordinal data while being robust to large sample sizes.

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1.70 score 1 scripts 125 downloads

OptimalDesign - A Toolbox for Computing Efficient Designs of Experiments

Algorithms for D-, A-, I-, and c-optimal designs. For more details, see the package description. Some of the functions in this package require the 'gurobi' software and its accompanying R package. For their installation, please follow the instructions at <https://www.gurobi.com> and the file gurobi_inst.txt, respectively.

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1.70 score 25 scripts 249 downloads

ADSIHT - Adaptive Double Sparse Iterative Hard Thresholding

Solving high-dimensional double sparse linear regression via an iterative hard thresholding algorithm. Furthermore, the method is extended to jointly estimate multiple graphical models. For more details, please see <https://www.jmlr.org/papers/v25/23-0653.html> and <doi:10.48550/arXiv.2503.18722>.

The purpose is to account for the random displacements (jittering) of true survey household cluster center coordinates in geostatistical analyses of Demographic and Health Surveys program (DHS) data. Adjustment for jittering can be implemented either in the spatial random effect, or in the raster/distance based covariates, or in both. Detailed information about the methods behind the package functionality can be found in our two papers. Umut Altay, John Paige, Andrea Riebler, Geir-Arne Fuglstad (2024) <doi:10.32614/RJ-2024-027>. Umut Altay, John Paige, Andrea Riebler, Geir-Arne Fuglstad (2023) <doi:10.1177/1471082X231219847>.

Shrinkage estimator for polygenic risk prediction (PRS) models based on summary statistics of genome-wide association (GWA) studies. Based upon the methods and original 'PANPRS' package as found in: Chen, Chatterjee, Landi, and Shi (2020) <doi:10.1080/01621459.2020.1764849>.

Provides an efficient and robust implementation for estimating marginal Hazard Ratio (HR) and Restricted Mean Survival Time (RMST) with covariate adjustment using Daniel et al. (2021) <doi:10.1002/bimj.201900297> and Karrison et al. (2018) <doi:10.1177/1740774518759281>.

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cpp

1.70 score 4 scripts 532 downloads

mermboost - Gradient Boosting for Generalized Additive Mixed Models

Provides a novel framework to estimate mixed models via gradient boosting. The implemented functions are based on the 'mboost' and 'lme4' packages, and the family range is therefore determined by 'lme4'. A correction mechanism for cluster-constant covariates is implemented, as well as estimation of the covariance of random effects. These methods are described in the accompanying publication; see <doi:10.1007/s11222-025-10612-y> for details.

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1.70 score 520 downloads

ipanema - Read Data from 'LimeSurvey'

Read data from 'LimeSurvey' (<https://www.limesurvey.org/>) in a comfortable way. Heavily inspired by 'limer' (<https://github.com/cloudyr/limer/>), which lacked a few comfort features for me.

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1.70 score 119 downloads

crossurr - Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers

Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D, Hejblum BP, Thiebaut R & Parast L (2022). "Doubly robust evaluation of high-dimensional surrogate markers", Biostatistics <doi:10.1093/biostatistics/kxac020>. You can use these methods to determine how much of the overall treatment effect is explained by a (possibly high-dimensional) set of surrogate markers.

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1.70 score 199 downloads

mongopipe - Write MongoDB Queries with R

Translate R code into MongoDB aggregation pipelines.

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1.70 score 3 scripts 292 downloads

cbq - Conditional Binary Quantile Models

Estimates conditional binary quantile models developed by Lu (2020) <doi:10.1017/pan.2019.29>. The estimation procedure is implemented based on Markov chain Monte Carlo methods.

ErlangC - Solve Erlang-C Model

Provides a set of functions to solve Erlang-C model. The Erlang C formula was invented by the Danish Mathematician A.K. Erlang and is used to calculate the number of advisors and the service level.

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1.70 score 3 scripts 163 downloads

graphicalEvidence - Graphical Evidence

Computes marginal likelihood in Gaussian graphical models through a novel telescoping block decomposition of the precision matrix which allows estimation of model evidence. The top level function used to estimate marginal likelihood is called evidence(), which expects the prior name, data, and relevant prior specific parameters. This package also provides an MCMC prior sampler using the same underlying approach, implemented in prior_sampling(), which expects a prior name and prior specific parameters. Both functions also expect the number of burn-in iterations and the number of sampling iterations for the underlying MCMC sampler.

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openblascppopenmp

1.70 score 616 downloads

hollr - Chat Completion and Text Annotation with Local and OpenAI Models

Enables chat completion and text annotation with local and 'OpenAI' <https://openai.com/> language models, supporting batch processing, multiple annotators, and consistent output formats.

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1.70 score 208 downloads

roseRF - ROSE Random Forests for Robust Semiparametric Efficient Estimation

ROSE (RObust Semiparametric Efficient) random forests for robust semiparametric efficient estimation in partially parametric models (containing generalised partially linear models). Details can be found in the paper by Young and Shah (2024) <doi:10.48550/arXiv.2410.03471>.

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1.70 score 2 scripts 218 downloads

logconcens - Maximum Likelihood Estimation of a Log-Concave Density Based on Censored Data

Based on right or interval censored data, compute the maximum likelihood estimator of a (sub)probability density under the assumption that it is log-concave. For further information see Duembgen, Rufibach and Schuhmacher (2014) <doi:10.1214/14-EJS930>.

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openblas

1.70 score 7 scripts 266 downloads

permutest - Run Permutation Tests and Construct Associated Confidence Intervals

Implements permutation tests for any test statistic and randomization scheme and constructs associated confidence intervals as described in Glazer and Stark (2024) <doi:10.48550/arXiv.2405.05238>.

A tool for fast, efficient bitwise operations along the elements within a vector. Provides such functionality for AND, OR and XOR, as well as infix operators for all of the binary bitwise operations.

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1.70 score 162 downloads

DeBoinR - Box-Plots and Outlier Detection for Probability Density Functions

Orders a data-set consisting of an ensemble of probability density functions on the same x-grid. Visualizes a box-plot of these functions based on the notion of distance determined by the user. Reports outliers based on the distance chosen and the scaling factor for an interquartile range rule. For further details, see: Alexander C. Murph et al. (2023). "Visualization and Outlier Detection for Probability Density Function Ensembles." <https://sirmurphalot.github.io/publications>.

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1.70 score 2 scripts 215 downloads

BayesFluxR - Implementation of Bayesian Neural Networks

Implementation of 'BayesFlux.jl' for R; It extends the famous 'Flux.jl' machine learning library to Bayesian Neural Networks. The goal is not to have the fastest production ready library, but rather to allow more people to be able to use and research on Bayesian Neural Networks.

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1.70 score 4 scripts 198 downloads

exceldata - Streamline Data Import, Cleaning and Recoding from 'Excel'

A small group of functions to read in a data dictionary and the corresponding data table from 'Excel' and to automate the cleaning, re-coding and creation of simple calculated variables. This package was designed to be a companion to the macro-enabled 'Excel' template available on the GitHub site, but works with any similarly-formatted 'Excel' data.

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1.70 score 1 stars 1 scripts 366 downloads

nlopt - Call Optimization Solvers with .nl Files

The purpose of this library is to to call different optimization solvers (such as Gonzalez Rodriguez et al. (2022) <doi:10.1007/s10898-022-01229-w>, Tawarmalani and Sahinidis (2005) <doi:10.1007/s10107-005-0581-8>, and Byrd et al. (2006) <doi:10.1007/0-387-30065-1_4>) to solve problems given by a standard nl file.

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1.70 score 2 scripts 372 downloads

MigrationDetectR - Segment-Based Migration Detection Algorithm

Detection of migration events and segments of continuous residence based on irregular time series of location data as published in Chi et al. (2020) <doi:10.1371/journal.pone.0239408>.

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1.70 score 1 scripts 152 downloads

BeQut - Bayesian Estimation for Quantile Regression Mixed Models

Using a Bayesian estimation procedure, this package fits linear quantile regression models such as linear quantile models, linear quantile mixed models, quantile regression joint models for time-to-event and longitudinal data. The estimation procedure is based on the asymmetric Laplace distribution and the 'JAGS' software is used to get posterior samples (Yang, Luo, DeSantis (2019) <doi:10.1177/0962280218784757>).

cpp

1.70 score 163 downloads

crrcbcv - Bias-Corrected Variance for Competing Risks Regression with Clustered Data

A user friendly function 'crrcbcv' to compute bias-corrected variances for competing risks regression models using proportional subdistribution hazards with small-sample clustered data. Four types of bias correction are included: the MD-type bias correction by Mancl and DeRouen (2001) <doi:10.1111/j.0006-341X.2001.00126.x>, the KC-type bias correction by Kauermann and Carroll (2001) <doi:10.1198/016214501753382309>, the FG-type bias correction by Fay and Graubard (2001) <doi:10.1111/j.0006-341X.2001.01198.x>, and the MBN-type bias correction by Morel, Bokossa, and Neerchal (2003) <doi:10.1002/bimj.200390021>.

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1.70 score 9 scripts 209 downloads

KingCountyHouses - Data on House Sales in King County WA

Data on houses in and around Seattle WA are included. Basic characteristics are given along with sale prices.

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1.70 score 10 scripts 240 downloads

droll - Analyze Roll Distributions

A toolkit for parsing dice notation, analyzing rolls, calculating success probabilities, and plotting outcome distributions.

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1.70 score 10 scripts 205 downloads

TensorClustering - Model-Based Tensor Clustering

Performs model-based tensor clustering methods including Tensor Gaussian Mixture Model (TGMM), Tensor Envelope Mixture Model (TEMM) by Deng and Zhang (2021) <DOI: 10.1111/biom.13486>, Doubly-Enhanced EM (DEEM) algorithm by Mai, Zhang, Pan and Deng (2021) <DOI: 10.1080/01621459.2021.1904959>.

The haversine is a function used to calculate the distance between a pair of latitude and longitude points while accounting for the assumption that the points are on a spherical globe. This package provides a fast, dataframe compatible, haversine function. For the first publication on the haversine calculation see Joseph de Mendoza y Ríos (1795) <https://books.google.cat/books?id=030t0OqlX2AC> (In Spanish).

dixon - Nearest Neighbour Contingency Table Analysis

Function to test spatial segregation and association based in contingency table analysis of nearest neighbour counts following Dixon (2002) <doi:10.1080/11956860.2002.11682700>. Some 'Fortran' code has been included to the original dixon2002() function of the 'ecespa' package to improve speed.

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1.68 score 1 dependents 16 scripts 385 downloads

ppmSuite - A Collection of Models that Employ Product Partition Distributions as a Prior on Partitions

Provides a suite of functions that fit models that use PPM type priors for partitions. Models include hierarchical Gaussian and probit ordinal models with a (covariate dependent) PPM. If a covariate dependent product partition model is selected, then all the options detailed in Page, G.L.; Quintana, F.A. (2018) <doi:10.1007/s11222-017-9777-z> are available. If covariate values are missing, then the approach detailed in Page, G.L.; Quintana, F.A.; Mueller, P (2020) <doi:10.1080/10618600.2021.1999824> is employed. Also included in the package is a function that fits a Gaussian likelihood spatial product partition model that is detailed in Page, G.L.; Quintana, F.A. (2016) <doi:10.1214/15-BA971>, and multivariate PPM change point models that are detailed in Quinlan, J.J.; Page, G.L.; Castro, L.M. (2023) <doi:10.1214/22-BA1344>. In addition, a function that fits a univariate or bivariate functional data model that employs a PPM or a PPMx to cluster curves based on B-spline coefficients is provided.

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1.68 score 2 stars 24 scripts 322 downloads

VBLPCM - Variational Bayes Latent Position Cluster Model for Networks

Fit and simulate latent position and cluster models for network data, using a fast Variational Bayes approximation developed in Salter-Townshend and Murphy (2013) <doi:10.1016/j.csda.2012.08.004>.

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gsl

1.68 score 2 stars 24 scripts 214 downloads

flexCWM - Flexible Cluster-Weighted Modeling

Allows maximum likelihood fitting of cluster-weighted models, a class of mixtures of regression models with random covariates. Methods are described in Angelo Mazza, Antonio Punzo, Salvatore Ingrassia (2018) <doi:10.18637/jss.v086.i02>.

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1.68 score 1 dependents 16 scripts 296 downloads

RDStreeboot - RDS Tree Bootstrap Method

A tree bootstrap method for estimating uncertainty in respondent-driven samples (RDS). Quantiles are estimated by multilevel resampling in such a way that preserves the dependencies of and accounts for the high variability of the RDS process.

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1.68 score 1 dependents 16 scripts 117 downloads

SpatialAcc - Spatial Accessibility Measures

Provides a set of spatial accessibility measures from a set of locations (demand) to another set of locations (supply). It aims, among others, to support research on spatial accessibility to health care facilities. Includes the locations and some characteristics of major public hospitals in Greece.

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1.67 score 1 stars 47 scripts 499 downloads

SPlit - Split a Dataset for Training and Testing

Procedure to optimally split a dataset for training and testing. 'SPlit' is based on the method of support points, which is independent of modeling methods. Please see Joseph and Vakayil (2021) <doi:10.1080/00401706.2021.1921037> for details. This work is supported by U.S. National Science Foundation grant DMREF-1921873.

Provides interpretable high-dimensional mean comparison methods (HMC). For example, users can apply these methods to assess the difference in gene expression between two treatment groups. It is not a gene-by-gene comparison. Instead, the methods focus on the interplay between features and identify those that are predictive of the group label. The tests are valid frequentist procedures and yield sparse estimates indicating which features contribute to the group differences.

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1.61 score 41 scripts 547 downloads

PermAlgo - Permutational Algorithm to Simulate Survival Data

This version of the permutational algorithm generates a dataset in which event and censoring times are conditional on an user-specified list of covariates, some or all of which are time-dependent.

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1.61 score 41 scripts 368 downloads

CompR - Paired Comparison Data Analysis

Different tools for describing and analysing paired comparison data are presented. Main methods are estimation of products scores according Bradley Terry Luce model. A segmentation of the individual could be conducted on the basis of a mixture distribution approach. The number of classes can be tested by the use of Monte Carlo simulations. This package deals also with multi-criteria paired comparison data.

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1.61 score 41 scripts 165 downloads

ProduceR - Concise and Efficient Tools for Everyday Statistical Production

A set of concise and efficient tools for statistical production. Can also be used for data management. In statistical production, you deal with complex data and need to control your process at each step of your work. Concise functions are very helpful, because you do not hesitate to use them. The following functions are included in the package. 'dup' checks duplicates. 'miss' checks missing values. 'tac' computes contingency table of all columns. 'toc' compares two tables, spotting significant deviations. 'chi2_find' compares columns within a data.frame, spotting related categories of (a more complex function).

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1.60 score 8 scripts 486 downloads

nmw - Understanding Nonlinear Mixed Effects Modeling for Population Pharmacokinetics

This shows how 'NONMEM' (Beal SL, Sheiner LB, Boeckmann AJ, Bauer RJ. NONMEM 7.5 Users Guides. Icon plc, 2020) software works. 'NONMEM' classical estimation methods such as 'First Order (FO) approximation', 'First Order Conditional Estimation (FOCE)', and 'Laplacian approximation' are explained. Functions are also provided for post-run processing of NONMEM output files, generating PDF diagnostic reports including objective function value analysis, parameter estimates, prediction and residual diagnostics, empirical Bayes estimate (EBE) analysis, input data summary, and individual pharmacokinetic parameter distributions. Helper utilities for building NONMEM-ready datasets from SDTM-style source tables are also included.

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1.60 score 1 stars 9 scripts 328 downloads

CompositionalClust - Clustering with Compositional Data

Cluster analysis with compositional data using the alpha--transformation. Relevant papers include: Tsagris M. and Kontemeniotis N. (2025). Lobachevskii Journal of Mathematics <doi:10.1134/S1995080225613700>. Tsagris M.T., Preston S. and Wood A.T.A. (2011), <doi:10.48550/arXiv.1106.1451>. Garcia-Escudero Luis A., Gordaliza Alfonso, Matran Carlos, Mayo-Iscar Agustin. (2008), <doi:10.1214/07-AOS515>.

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1.60 score 144 downloads

estadistica - Fundamentos de estadística descriptiva e inferencial

Este paquete pretende apoyar el proceso enseñanza-aprendizaje de estadística descriptiva e inferencial. Las funciones contenidas en el paquete 'estadistica' cubren los conceptos básicos estudiados en un curso introductorio. Muchos conceptos son ilustrados con gráficos dinámicos o web apps para facilitar su comprensión. This package aims to help the teaching-learning process of descriptive and inferential statistics. The functions contained in the package 'estadistica' cover the basic concepts studied in a statistics introductory course. Many concepts are illustrated with dynamic graphs or web apps to make the understanding easier. See: Esteban et al. (2005, ISBN: 9788497323741), Newbold et al.(2019, ISBN:9781292315034 ), Murgui et al. (2002, ISBN:9788484424673) .

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1.60 score 2 scripts 859 downloads

nnmf - Nonnegative Matrix Factorization

Nonnegative matrix factorization (NMF) is a technique to factorize a matrix with nonnegative values into the product of two matrices. Covariates are also allowed. Parallel computing is an option to enhance the speed and high-dimensional and large scale (and/or sparse) data are allowed. Relevant papers include: Wang Y. X. and Zhang Y. J. (2012). Nonnegative matrix factorization: A comprehensive review. IEEE Transactions on Knowledge and Data Engineering, 25(6): 1336-1353 <doi:10.1109/TKDE.2012.51> and Kim H. and Park H. (2008). Nonnegative matrix factorization based on alternating nonnegativity constrained least squares and active set method. SIAM Journal on Matrix Analysis and Applications, 30(2): 713-730 <doi:10.1137/07069239X>.

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cppopenmp

1.60 score 3 scripts 511 downloads

Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.

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1.60 score 2 stars 683 downloads

MSclassifR - Automated Classification of Mass Spectra

Functions to classify mass spectra in known categories and to determine discriminant mass-to-charge values (m/z). Includes easy-to-use preprocessing pipelines for Matrix Assisted Laser Desorption Ionisation - Time Of Flight Mass Spectrometry (MALDI-TOF) mass spectra, methods to select discriminant m/z from labelled libraries, and tools to predict categories (species, phenotypes, etc.) from selected features. Also provides utilities to build design matrices from peak intensities and labels. While this package was developed with the aim of identifying very similar species or phenotypes of bacteria from MALDI-TOF MS, the functions of this package can also be used to classify other categories associated to mass spectra; or from mass spectra obtained with other mass spectrometry techniques. Parallelized processing and optional C++-accelerated functions are available (notably to deal with large datasets) from version 0.5.0. If you use this package in your research, please cite the associated publication (<doi:10.1016/j.eswa.2025.128796>). For a comprehensive guide, additional applications, and detailed examples, see <https://github.com/agodmer/MSclassifR_examples>.

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1.48 score 1 dependents 2 scripts 215 downloads

CatReg - Solution Paths for Linear and Logistic Regression Models with Categorical Predictors, with SCOPE Penalty

Computes solutions for linear and logistic regression models with potentially high-dimensional categorical predictors. This is done by applying a nonconvex penalty (SCOPE) and computing solutions in an efficient path-wise fashion. The scaling of the solution paths is selected automatically. Includes functionality for selecting tuning parameter lambda by k-fold cross-validation and early termination based on information criteria. Solutions are computed by cyclical block-coordinate descent, iterating an innovative dynamic programming algorithm to compute exact solutions for each block.

R functions for the computation of the truncated maximum likelihood and the robust accelerated failure time regression for gaussian and log-Weibull case.

1.34 score 22 scripts 180 downloads

mmeta - Multivariate Meta-Analysis

Multiple 2 by 2 tables often arise in meta-analysis which combines statistical evidence from multiple studies. Two risks within the same study are possibly correlated because they share some common factors such as environment and population structure. This package implements a set of novel Bayesian approaches for multivariate meta analysis when the risks within the same study are independent or correlated. The exact posterior inference of odds ratio, relative risk, and risk difference given either a single 2 by 2 table or multiple 2 by 2 tables is provided. Luo, Chen, Su, Chu, (2014) <doi:10.18637/jss.v056.i11>, Chen, Luo, (2011) <doi:10.1002/sim.4248>, Chen, Chu, Luo, Nie, Chen, (2015) <doi:10.1177/0962280211430889>, Chen, Luo, Chu, Su, Nie, (2014) <doi:10.1080/03610926.2012.700379>, Chen, Luo, Chu, Wei, (2013) <doi:10.1080/19466315.2013.791483>.

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1.34 score 22 scripts 252 downloads

BSSasymp - Asymptotic Covariance Matrices of Some BSS Mixing and Unmixing Matrix Estimates

Functions to compute the asymptotic covariance matrices of mixing and unmixing matrix estimates of the following blind source separation (BSS) methods: symmetric and squared symmetric FastICA, regular and adaptive deflation-based FastICA, FOBI, JADE, AMUSE and deflation-based and symmetric SOBI. Also functions to estimate these covariances based on data are available.

catekappa - Design and Analysis of Consistency Tests Based on Kappa Statistic

Provides a 'Shiny' application and supporting functions for the design and analysis of consistency tests based on Kappa statistic with categorical responses. Wraps 'irr' and 'kappaSize' packages.

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1.30 score 113 downloads

CompositionalNAimp - Missing Value Imputation with Compositional Data

Functions to perform missing value imputation with compositional data using the Jensen-Shannon divergence based k--NN and a--k--NN algorithms. The functions are based on the following paper: Tsagris M., Alenazi A. and Stewart C. (2026). "A Jensen--Shannon divergence based k--NN algorithm for missing value imputation in compositional data", <doi:10.1080/02664763.2026.2677908>.

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1.30 score 155 downloads

rapidcodeR - Optimized Data Analysis System for AI-Based Text Processing

Extracts machine-readable variables from natural language text using AI APIs. Optimized for speed and cost efficiency through parallel processing and direct CSV-formatted responses from language models. Supports multiple AI providers with robust error handling and automatic retry mechanisms for failed extractions.

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1.30 score 1 stars 506 downloads

PGaovR - Analysis of Experimental Data using ANOVA and Mean Comparison

Provides tools for designing and analyzing agricultural experiments. It includes functions for generating randomized treatment layouts for standard experimental designs such as Completely Randomized Design (CRD), Randomized Block Design (RBD), Latin Square Design (LSD), Factorial Randomized Block Design (FRBD), split-plot design, and strip-plot design. The package implements one-factor and two-factor analysis of variance (ANOVA) and offers multiple comparison procedures, including Least Significant Difference (lsd), Tukey, and Duncan tests, to compare treatment means in single-factor and factorial experiments. The methods follow classical experimental design principles described in Gomez and Gomez (1984, Statistical Procedures for Agricultural Research, John Wiley & Sons, New York).

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1.30 score 283 downloads

BoundIRT - Fit Bounded Continuous Item Response Theory Models to Data

Bounded continuous data are encountered in many areas of test application. Examples include visual analogue scales used in the measurement of personality, mood, depression, and quality of life; item response times from tests with item deadlines; confidence ratings; and pain intensity ratings. Using this package, item response theory (IRT) models suitable for bounded continuous item scores can be fitted to data within a Bayesian framework. The package draws on posterior sampling facilities provided by R-package 'rstan' (Stan Development Team, 2025)<https://mc-stan.org/>. Available models include the Beta IRT model by Noel and Dauvier (2007)<doi:10.1177/0146621605287691>, the continuous response model by Samejima (1973)<doi:10.1007/BF03372160>, the unbounded normal model by Mellenbergh (1994)<doi:10.1207/s15327906mbr2903_2>, and the Simplex IRT model by Flores et al. (2020)<doi:10.1007/978-3-030-43469-4_8>. All models can be fitted with or without zero-one inflation (Molenaar et al., 2022)<doi:10.3102/10769986221108455>. Model fit comparisons can be conducted using the Watanabe-Akaike information criterion (WAIC), leave-one-out cross-validation information citerion (LOOIC) and the fully marginalized likelihood (i.e., Bayes factors).

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cpp

1.30 score 303 downloads

sc2sc - Spatial Transfer of Statistics among Spanish Census Sections

Transfers/imputes statistics among Spanish spatial polygons (census sections or postal code areas) from different moments in time (2001-2026) without need of spatial files, just linking statistics to the ID codes of the spatial units. The data available in the census sections of a partition/division (cartography) into force in a moment of time is transferred to the census sections of another partition/division employing the geometric approach (also known as areal weighting or polygon overlay). References: Goerlich (2022) <doi:10.12842/WPIVIE_0322>. Pavía and Cantarino (2017a, b) <doi:10.1111/gean.12112>, <doi:10.1016/j.apgeog.2017.06.021>. Pérez and Pavía (2024a, b) <doi:10.4995/CARMA2024.2024.17796>, <doi:10.38191/iirr-jorr.24.057>. Acknowledgements: The authors wish to thank Consellería de Educación, Cultura, Universidades y Empleo, Generalitat Valenciana (grant CIACIO/2023/031), Consellería de Educación, Universidades y Empleo, Generalitat Valenciana (grant AICO/2021/257), Ministerio de Economía e Innovación (grant PID2021-128228NB-I00) and Fundación Mapfre for supporting this research.

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1.30 score 1 stars 530 downloads

CurricularComplexityData - Data for Exploring Curricular Complexity

Provides 'igraph' objects representing engineering plans of study across multiple disciplines and institutions. The data are intended for use with the 'CurricularComplexity' package (Reeping, 2026) <doi:10.32614/CRAN.package.CurricularComplexity> to support analyses of curricular structure.

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1.30 score 416 downloads

PhaseGMM - Phase-Function Based Estimation and Inference for Linear Errors-in-Variables (EIV) Models

Estimation and inference for coefficients of linear EIV models with symmetric measurement errors. The measurement errors can be homoscedastic or heteroscedastic, for the latter, replication for at least some observations needs to be available. The estimation method and asymptotic inference are based on a generalised method of moments framework, where the estimating equations are formed from (1) minimising the distance between the empirical phase function (normalised characteristic function) of the response and that of the linear combination of all the covariates at the estimates, and (2) minimising a corrected least-square discrepancy function. Specifically, for a linear EIV model with p error-prone and q error-free covariates, if replicates are available, the GMM approach is based on a 2(p+q) estimating equations if some replicates are available and based on p+2q estimating equations if no replicate is available. The details of the method are described in Nghiem and Potgieter (2020) <doi:10.1093/biomet/asaa025> and Nghiem and Potgieter (2025) <doi:10.5705/ss.202022.0331>.

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1.30 score 421 downloads

ccLRforR - Case-Control Likelihood Ratio (ccLR)

Implementation of case-control data analysis using likelihood ratio approaches and logistic regression for the classification of variants of uncertain significance (VUS) in breast, ovarian, or custom cancer susceptibility genes.

FactorCopulaModel - Factor Copula Models

Inference methods for factor copula models for continuous data in Krupskii and Joe (2013) <doi:10.1016/j.jmva.2013.05.001>, Krupskii and Joe (2015) <doi:10.1016/j.jmva.2014.11.002>, Fan and Joe (2024) <doi:10.1016/j.jmva.2023.105263>, one factor truncated vine models in Joe (2018) <doi:10.1002/cjs.11481>, and Gaussian oblique factor models. Functions for computing tail-weighted dependence measures in Lee, Joe and Krupskii (2018) <doi:10.1080/10485252.2017.1407414> and estimating tail dependence parameter.

Implementation of the LoTTA (Local Trimmed Taylor Approximation) model described in "Bayesian Regression Discontinuity Design with Unknown Cutoff" by Kowalska, van de Wiel, van der Pas (2024) <doi:10.48550/arXiv.2406.11585>.

kpcaIG - Variables Interpretability with Kernel PCA

The kernelized version of principal component analysis (KPCA) has proven to be a valid nonlinear alternative for tackling the nonlinearity of biological sample spaces. However, it poses new challenges in terms of the interpretability of the original variables. 'kpcaIG' aims to provide a tool to select the most relevant variables based on the kernel PCA representation of the data as in Briscik et al. (2023) <doi:10.1186/s12859-023-05404-y>. It also includes functions for 2D and 3D visualization of the original variables (as arrows) into the kernel principal components axes, highlighting the contribution of the most important ones.

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1.30 score 2 stars 2 scripts 112 downloads

fastPLS - A Fast Implementation of Partial Least Square

An implementation in 'Rcpp' / 'RcppArmadillo' of Partial Least Square algorithms. This package includes other functions to perform the double cross-validation and a fast correlation.

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openblascpp

1.30 score 20 scripts 147 downloads

RsSimulx - Extension of 'lixoftConnectors' for 'Simulx'

Provides useful tools which supplement the use of 'Simulx' software and 'R' connectors ('Monolix Suite'). 'Simulx' is an easy, efficient and flexible application for clinical trial simulations. You need 'Simulx' software to be installed in order to use 'RsSimulx' package. Among others tasks, 'RsSimulx' provides the same functions as package 'mlxR' does with a compatibility with 'Simulx' software.

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1.30 score 2 stars 4 scripts 288 downloads

psbcGroup - Penalized Parametric and Semiparametric Bayesian Survival Models with Shrinkage and Grouping Priors

Algorithms to implement various Bayesian penalized survival regression models including: semiparametric proportional hazards models with lasso priors (Lee et al., Int J Biostat, 2011 <doi:10.2202/1557-4679.1301>) and three other shrinkage and group priors (Lee et al., Stat Anal Data Min, 2015 <doi:10.1002/sam.11266>); parametric accelerated failure time models with group/ordinary lasso prior (Lee et al. Comput Stat Data Anal, 2017 <doi:10.1016/j.csda.2017.02.014>).

AntAngioCOOL - Anti-Angiogenic Peptide Prediction

Machine learning based package to predict anti-angiogenic peptides using heterogeneous sequence descriptors. 'AntAngioCOOL' exploits five descriptor types of a peptide of interest to do prediction including: pseudo amino acid composition, k-mer composition, k-mer composition (reduced alphabet), physico-chemical profile and atomic profile. According to the obtained results, 'AntAngioCOOL' reached to a satisfactory performance in anti-angiogenic peptide prediction on a benchmark non-redundant independent test dataset.

Implementation of the Density Ratio Permutation Test for testing the goodness-of-fit of a hypothesised ratio of two densities, as described in Bordino and Berrett (2025) <doi:10.48550/arXiv.2505.24529>.

Compute important quantities when we consider stochastic systems that are observed continuously. Such as, Cost model, Limiting distribution, Transition matrix, Transition distribution and Occupancy matrix. The methods are described, for example, Ross S. (2014), Introduction to Probability Models. Eleven Edition. Academic Press.

Computes maximum mean discrepancy two-sample test for univariate data using the Laplacian kernel, as described in Bodenham and Kawahara (2023) <doi:10.1007/s11222-023-10271-x>. The p-value is computed using permutations. Also includes implementation for computing the robust median difference statistic 'Q_n' from Croux and Rousseeuw (1992) <doi:10.1007/978-3-662-26811-7_58> based on Johnson and Mizoguchi (1978) <doi:10.1137/0207013>.

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cpp

1.20 score 16 scripts 213 downloads

wavScalogram - Wavelet Scalogram Tools for Time Series Analysis

Provides scalogram based wavelet tools for time series analysis: wavelet power spectrum, scalogram, windowed scalogram, windowed scalogram difference (see Bolos et al. (2017) <doi:10.1016/j.amc.2017.05.046>), scale index and windowed scale index (Benitez et al. (2010) <doi:10.1016/j.camwa.2010.05.010>).

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1.20 score 16 scripts 290 downloads

LS2Wstat - A Multiscale Test of Spatial Stationarity for LS2W Processes

Wavelet-based methods for testing stationarity and quadtree segmenting of images, see Taylor et al (2014) <doi:10.1080/00401706.2013.823890>.

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1.20 score 1 stars 16 scripts 184 downloads

ProbitSpatial - Probit with Spatial Dependence, SAR, SEM and SARAR Models

Fast estimation of binomial spatial probit regression models with spatial autocorrelation for big datasets.

A finite mixture of Zero-Inflated Poisson (ZIP) models for analyzing criminal trajectories.

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openblasfortranglibc

1.18 score 15 scripts 345 downloads

gsrsb - Group Sequential Refined Secondary Boundary

A gate-keeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Computations related to group sequential primary and secondary boundaries. Refined secondary boundaries are calculated for a gate-keeping test on a primary and a secondary endpoint in a group sequential design with multiple interim looks. The choices include both the standard boundaries and the boundaries using error spending functions. See Tamhane et al. (2018), "A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks", Biometrics, 74(1), 40-48.

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1.18 score 15 scripts 197 downloads

BondValuation - Fixed Coupon Bond Valuation Allowing for Odd Coupon Periods and Various Day Count Conventions

Analysis of large datasets of fixed coupon bonds, allowing for irregular first and last coupon periods and various day count conventions. With this package you can compute the yield to maturity, the modified and MacAulay durations and the convexity of fixed-rate bonds. It provides the function AnnivDates, which can be used to evaluate the quality of the data and return time-invariant properties and temporal structure of a bond.

SeleMix - Selective Editing via Mixture Models

Detection of outliers and influential errors using a latent variable model.

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1.08 score 12 scripts 568 downloads

Contains three simulation functions for implementing the entire Phase 123 trial and the separate Eff-Tox and Phase 3 portions of the trial, which may be beneficial for use on clusters. The functions AssignEffTox() and RandomizeEffTox() assign doses to patient cohorts during phase 12 and Reoptimize() determines the optimal dose to continue with during Phase 3. The functions ReturnMeansAgent() and ReturnMeanControl() gives the true mean survival for the agent doses and control and ReturnOCS() gives the operating characteristics of the design.

Routines for estimating tree fiber (tracheid) length distributions in the standing tree based on increment core samples. Two types of data can be used with the package, increment core data measured by means of an optical fiber analyzer (OFA), e.g. such as the Kajaani Fiber Lab, or measured by microscopy. Increment core data analyzed by OFAs consist of the cell lengths of both cut and uncut fibres (tracheids) and fines (such as ray parenchyma cells) without being able to identify which cells are cut or if they are fines or fibres. The microscopy measured data consist of the observed lengths of the uncut fibres in the increment core. A censored version of a mixture of the fine and fiber length distributions is proposed to fit the OFA data, under distributional assumptions (Svensson et al., 2006) <doi:10.1111/j.1467-9469.2006.00501.x>. The package offers two choices for the assumptions of the underlying density functions of the true fiber (fine) lenghts of those fibers (fines) that at least partially appear in the increment core, being the generalized gamma and the log normal densities.

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cpp

1.04 score 11 scripts 183 downloads

rPAex - Automatic Detection of Experimental Unit in Precision Agriculture

A part of precision agriculture is linked to the spectral image obtained from the cameras. With the image information of the agricultural experiment, the included functions facilitate the collection of spectral data associated with the experimental units. Some designs generated in R are linked to the images, which allows the use of the information of each pixel of the image in the experimental unit and the treatment. Tables and images are generated for the analysis of the precision agriculture experiment during the entire vegetative period of the crop.

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1.04 score 11 scripts 158 downloads

GameTheory - Cooperative Game Theory

Implementation of a common set of punctual solutions for Cooperative Game Theory.

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1.04 score 11 scripts 294 downloads

indelmiss - Insertion Deletion Analysis While Accounting for Possible Missing Data

Genome-wide gene insertion and deletion rates can be modelled in a maximum likelihood framework with the additional flexibility of modelling potential missing data using the models included within. These models simultaneously estimate insertion and deletion (indel) rates of gene families and proportions of "missing" data for (multiple) taxa of interest. The likelihood framework is utilized for parameter estimation. A phylogenetic tree of the taxa and gene presence/absence patterns (with data ordered by the tips of the tree) are required. See Dang et al. (2016) <doi:10.1534/genetics.116.191973> for more details.

MCPtests - Multiples Comparisons Procedures

Performs the execution of the main procedures of multiple comparisons in the literature, Scott-Knott (1974) <http://www.jstor.org/stable/2529204>, Batista (2016) <http://repositorio.ufla.br/jspui/handle/1/11466>, including graphic representations and export to different extensions of its results. An additional part of the package is the presence of the performance evaluation of the tests (Type I error per experiment and the power). This will assist the user in making the decision for the chosen test.

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1.04 score 11 scripts 239 downloads

dundermifflin - The Office Quotes on-Demand

Provides functions to randomly select, return, and print quotes or entire scenes from the American version of the show the Office. Receive laughs from one of of the greatest sitcoms of all time on demand. Add these functions to your '.Rprofile' to get a good laugh everytime you start a new R session.

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1.04 score 11 scripts 235 downloads

TUWmodel - Lumped/Semi-Distributed Hydrological Model for Education Purposes

The model, developed at the Vienna University of Technology, is a lumped conceptual rainfall-runoff model, following the structure of the HBV model. The model can also be run in a semi-distributed fashion and with dual representation of soil layer. The model runs on a daily or shorter time step and consists of a snow routine, a soil moisture routine and a flow routing routine. See Parajka, J., R. Merz, G. Bloeschl (2007) <DOI:10.1002/hyp.6253> Uncertainty and multiple objective calibration in regional water balance modelling: case study in 320 Austrian catchments, Hydrological Processes, 21, 435-446.

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1.04 score 1 stars 11 scripts 323 downloads

detpack - Density Estimation and Random Number Generation with Distribution Element Trees

Density estimation for possibly large data sets and conditional/unconditional random number generation or bootstrapping with distribution element trees. The function 'det.construct' translates a dataset into a distribution element tree. To evaluate the probability density based on a previously computed tree at arbitrary query points, the function 'det.query' is available. The functions 'det1' and 'det2' provide density estimation and plotting for one- and two-dimensional datasets. Conditional/unconditional smooth bootstrapping from an available distribution element tree can be performed by 'det.rnd'. For more details on distribution element trees, see: Meyer, D.W. (2016) <arXiv:1610.00345> or Meyer, D.W., Statistics and Computing (2017) <doi:10.1007/s11222-017-9751-9> and Meyer, D.W. (2017) <arXiv:1711.04632> or Meyer, D.W., Journal of Computational and Graphical Statistics (2018) <doi:10.1080/10618600.2018.1482768>.

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1.04 score 11 scripts 140 downloads

robustreg - Robust Regression Functions

Linear regression functions using Huber and bisquare psi functions. Optimal weights are calculated using IRLS algorithm.

nirs4alldatasets - Acquire Curated NIRS Reference Datasets ('nirs4all-datasets')

R binding over the 'nirs4all-datasets' C 'ABI' ('n4ds_*'): resolve a dataset id from the distributable catalog index into a version-pinned download contract, fetch the canonical 'Parquet' ('Dataverse' / 'Zenodo' / 'figshare') with SHA-256 verification into a local cache, and re-verify a cached directory offline. JSON crosses the stable C 'ABI'; analysis of the data is left to the host.

Estimates RxC (R by C) vote transfer matrices (ecological contingency tables) from aggregate data building on Thomsen (1987) and Park (2008) approaches. References: Park, W.-H. (2008). ''Ecological Inference and Aggregate Analysis of Election''. PhD Dissertation. University of Michigan. <https://deepblue.lib.umich.edu/bitstream/handle/2027.42/58525/wpark_1.pdf> Pavía, J.M. and Thomsen, S.R. (2025) ''ecolRxC: Ecological inference estimation of RxC tables using latent structure approaches''. Political Science Research and Methods, 13(4), 943-961. <doi:10.1017/psrm.2024.57> Thomsen, S.R. (1987, ISBN:87-7335-037-2). ''Danish Elections 1920 79: a Logit Approach to Ecological Analysis and Inference''. Politica, Aarhus, Denmark. Acknowledgements: The authors wish to thank Generalitat Valenciana (Conselleria de Educacion, Cultura y Universidades), grant CIACIO/2023/031, and Ministerio de Economia e Innovacion, grant PID2021-128228NB-I00, for supporting this research.

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cpp

1.00 score 3 scripts 388 downloads

rocTools - Tools for Distribution-Based ROC Smoothing Using 'pROC'

Extends the functionality of the 'pROC' package for conducting smoothed receiver operating characteristic (ROC) curve analysis. Enables automated selection of the distribution families to be fit when smoothing ROC curves via the population probability density function estimation strategy described by Leeflang et al. (2008) <doi:10.1373/clinchem.2007.096032>, as well as generation of diagnostic performance and cutoff estimates from the resultant smoothed curves.

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1.00 score 249 downloads

KMT - Khmaladze Martingale Transformation Goodness-of-Fit Test

Consider a goodness-of-fit problem of testing whether a random sample comes from one sample location-scale model where location and scale parameters are unknown. It is well known that Khmaladze-martingale-transformation method proposed by Khmaladze (1981) <doi:10.1137/1126027> provides asymptotic distribution free test. This package provides test statistic and critical value of the test for normal, Cauchy, and logistic distributions. This package used the main algorithm proposed by Kim (2020) <doi:10.1007/s00180-020-00971-7> and tests for other distributions will be available at the later version.

Provides implementations of origin-based and symmetrized minimum covariance determinant (MCD) estimators, together with supporting utility functions.

Supports propensity score-based methods—including matching, stratification, and weighting—for estimating causal treatment effects. It also implements calibration using negative control outcomes to enhance robustness. 'debiasedTrialEmulation' facilitates effect estimation for both binary and time-to-event outcomes, supporting risk ratio (RR), odds ratio (OR), and hazard ratio (HR) as effect measures. It integrates statistical modeling and visualization tools to assess covariate balance, equipoise, and bias calibration. Additional methods—including approaches to address immortal time bias, information bias, selection bias, and informative censoring—are under development. Users interested in these extended features are encouraged to contact the package authors.

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1.00 score 1 stars 237 downloads

DESNP - Differentially Expressed Single Nucleotide Polymorphism

Provides a framework for the identification and analysis of Differentially Expressed Single Nucleotide Polymorphisms (deSNPs) using high-throughput sequencing data. It enables users to import SNP count data from variant files, perform allele-specific read count extraction, and statistically detect SNPs showing significant differences in allele expression between biological conditions or sample groups. This package contains tools for calculating SNP-index and Delta SNP-index from VCF-derived allele depth data with statistical testing and filtering, including sliding-window analysis of genomic regions.

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1.00 score 488 downloads

eiCircles - Ecological Inference of RxC Tables by Overdispersed-Multinomial Models

Estimates RxC (R by C) vote transfer matrices (ecological contingency tables) from aggregate data using the model described in Forcina et al. (2012), as extension of the model proposed in Brown and Payne (1986). Allows incorporation of covariates. References: Brown, P. and Payne, C. (1986). ''Aggregate data, ecological regression and voting transitions''. Journal of the American Statistical Association, 81, 453–460. <DOI:10.1080/01621459.1986.10478290>. Forcina, A., Gnaldi, M. and Bracalente, B. (2012). ''A revised Brown and Payne model of voting behaviour applied to the 2009 elections in Italy''. Statistical Methods & Applications, 21, 109–119. <DOI:10.1007/s10260-011-0184-x>. Pavia, J.M, and Forcina, A. (2026). ''Simulating electoral behavior''. Modeling Decisions for Artificial Intelligence, MDAI 2025. Lecture Notes in Computer Science, vol 15957, Torra, V., Narukawa, Y., Domingo-Ferrer, J. (eds), Springer, Cham, pp. 54-65. <DOI:10.1007/978-3-032-00891-6_5>. Acknowledgements: The authors wish to thank Consellería de Educación, Cultura, Universidades y Empleo, Generalitat Valenciana (grant CIAICO/2023/031) and MICIU/AEI/10.13039/501100011033/FEDER, EU (grant PID2021-128228NB-I00) for supporting this research.

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1.00 score 1 scripts 511 downloads

ergmclust - Exponential-Family Random Graph Models for Network Clustering

Implements clustering and estimates parameters in Exponential-Family Random Graph Models for static undirected and directed networks, developed in Vu et al. (2013) <https://projecteuclid.org/euclid.aoas/1372338477>.

Allows for production of Czekanowski's Diagrams with clusters. See K. Bartoszek, A. Vasterlund (2020) <doi:10.2478/bile-2020-0008> and K. Bartoszek, Y. Luo (2023) <doi:10.14708/ma.v51i2.7259>. The suggested 'FuzzyDBScan' package (which allows for fuzzy clustering) can be obtained from <https://github.com/henrifnk/FuzzyDBScan/> (or from CRAN's Archive <https://cran.r-project.org/src/contrib/Archive/FuzzyDBScan/>).

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1.00 score 6 scripts 597 downloads

Pacote para a analise de experimentos havendo duas variaveis explicativas quantitativas e uma variavel dependente quantitativa. Os experimentos podem ser sem repeticoes ou com delineamento estatistico. Sao ajustados 12 modelos de regressao multipla e plotados graficos de superficie resposta (Hair JF, 2016) <ISBN:13:978-0138132637>.(Package for the analysis of experiments having two explanatory quantitative variables and one quantitative dependent variable. The experiments can be without repetitions or with a statistical design. Twelve multiple regression models are fitted and response surface graphs are plotted (Hair JF, 2016) <ISBN:13:978-0138132637>).

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1.00 score 247 downloads

irls - Generalised Linear Models via Iteratively Reweighted Least Squares

Generalised linear models via the iteratively reweighted least squares algorithm. The functions perform logistic, Poisson and Gamma regression (ISBN:9780412317606), either for a single model or many regression models in a column-wise fashion.

Implements exact, normally approximated, and sampling-based sensitivity analysis for observational studies with contingency tables. Includes exact (kernel-based), normal approximation, and sequential importance sampling (SIS) methods using 'Rcpp' for computational efficiency. The methods build upon the framework introduced in Rosenbaum (2002) <doi:10.1007/978-1-4757-3692-2> and the generalized design sensitivity framework developed by Chiu (2025) <doi:10.48550/arXiv.2507.17207>.

LePage - LePage Type Tests

Location and scale hypothesis testing using the LePage test and variants of its as proposed by Hussain A. and Tsagris M. (2025), <doi:10.48550/arXiv.2509.19126>.

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1.00 score 133 downloads

BlockwiseRankTest - Block-Wise Rank in Similarity Graph Edge-Count Two-Sample Test (BRISE)

Implements the Block-wise Rank in Similarity Graph Edge-count test (BRISE), a rank-based two-sample test designed for block-wise missing data. The method constructs (pattern) pair-wise similarity graphs and derives quadratic test statistics with asymptotic chi-square distribution or permutation-based p-values. It provides both vectorized and congregated versions for flexible inference. The methodology is described in Zhang, Liang, Maile, and Zhou (2025) <doi:10.48550/arXiv.2508.17411>.

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1.00 score 130 downloads

FDOTT - Optimal Transport Based Testing in Factorial Design

Perform optimal transport based tests in factorial designs as introduced in Groppe et al. (2025) <doi:10.48550/arXiv.2509.13970> via the FDOTT() function. These tests are inspired by ANOVA and its nonparametric counterparts. They allow for testing linear relationships in factorial designs between finitely supported probability measures on a metric space. Such relationships include equality of all measures (no treatment effect), interaction effects between a number of factors, as well as main and simple factor effects.

Methods and tools for forecasting univariate time series using the NARFIMA (Neural AutoRegressive Fractionally Integrated Moving Average) model. It combines neural networks with fractional differencing to capture both nonlinear patterns and long-term dependencies. The NARFIMA model supports seasonal adjustment, Box-Cox transformations, optional exogenous variables, and the computation of prediction intervals. In addition to the NARFIMA model, this package provides alternative forecasting models including NARIMA (Neural ARIMA), NBSTS (Neural Bayesian Structural Time Series), and NNaive (Neural Naive) for performance comparison across different modeling approaches. The methods are based on algorithms introduced by Chakraborty et al. (2025) <doi:10.48550/arXiv.2509.06697>.

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1.00 score 193 downloads

gridOT - Approximate Optimal Transport Between Two-Dimensional Grids

Can be used for optimal transport between two-dimensional grids with respect to separable cost functions of l^p form. It utilizes the Frank-Wolfe algorithm to approximate so-called pivot measures: One-dimensional transport plans that fully describe the full transport, see G. Auricchio (2023) <doi:10.4171/RLM/1026>. For these, it offers methods for visualization and to extract the corresponding transport plans and costs. Additionally, related functions for one-dimensional optimal transport are available.

Sequential change-point tests, parameters estimation, and goodness-of-fit tests for generalized Ornstein-Uhlenbeck processes.

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1.00 score 491 downloads

CTxCC - Multivariate Normal Mean Monitoring Through Critical-to-X Control Chart

A comprehensive set of functions designed for multivariate mean monitoring using the Critical-to-X Control Chart. These functions enable the determination of optimal control limits based on a specified in-control Average Run Length (ARL), the calculation of out-of-control ARL for a given control limit, and post-signal analysis to identify the specific variable responsible for a detected shift in the mean. This suite of tools provides robust support for precise and effective process monitoring and analysis.

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1.00 score 588 downloads

EQUALencrypt - Encryption and Decryption of Files and Data for Researchers Without Coding Skills

Support functions for R-based "EQUALencrypt - Encrypt and decrypt whole files" and "EQUALencrypt - Encrypt and decrypt columns of data" shiny applications which allow researchers without coding skills or expertise in encryption algorithms to share data after encryption. Gurusamy,K (2025)<doi:10.5281/zenodo.16743676> and Gurusamy,K (2025)<doi:10.5281/zenodo.16744058>.

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1.00 score 173 downloads

extrafrail - Estimation and Additional Tools for Alternative Shared Frailty Models

Provide estimation and data generation tools for new multivariate frailty models. This version includes the gamma, inverse Gaussian, weighted Lindley, Birnbaum-Saunders, truncated normal, mixture of inverse Gaussian, mixture of Birnbaum-Saunders, generalized exponential and Jorgensen-Seshadri-Whitmore as the distribution for frailty terms. For the basal model, it is considered a parametric approach based on the exponential, Weibull and the piecewise exponential distributions as well as a semiparametric approach. For details, see Gallardo et al. (2024) <doi:10.1007/s11222-024-10458-w>, Gallardo et al. (2025) <doi:10.1002/bimj.70044>, Kiprotich et al. (2025) <doi:10.1177/09622802251338984> and Gallardo et al. (2025) <doi:10.1038/s41598-025-15903-y>.

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1.00 score 305 downloads

Provides functions for carrying out nonparametric hypothesis tests of the MCAR hypothesis based on the theory of Frechet classes and compatibility. Also gives functions for computing halfspace representations of the marginal polytope and related geometric objects.

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cpp

1.00 score 3 scripts 198 downloads

ggmRSCU - Visualizing Multi-Species Relative Synonymous Codon Usage and Extensible Data Exploration

Facilitates efficient visualization of Relative Synonymous Codon Usage patterns across species. Based on analytical outputs from 'codonW', 'MEGA', and 'Phylosuite', it supports multi-species 'RSCU' comparisons and allows users to explore visual analysis of structurally similar datasets.

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1.00 score 2 scripts 180 downloads

extractFAERS - Extract Data from FAERS Database

Provides functions to extract and process data from the FDA Adverse Event Reporting System (FAERS). It facilitates the conversion of raw FAERS data published after 2014Q3 into structured formats for analysis. See Yang et al. (2022) <doi:10.3389/fphar.2021.772768> for related information.

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1.00 score 1 stars 164 downloads

spphpr - Spring Phenological Prediction

Predicts the occurrence times (in day-of-year) of spring phenological events. Three methods, including the accumulated degree days (ADD) method, the accumulated days transferred to a standardized temperature (ADTS) method, and the accumulated developmental progress (ADP) method, were used. See Shi et al. (2017a) <doi:10.1016/j.agrformet.2017.04.001> and Shi et al. (2017b) <doi:10.1093/aesa/sax063> for details.

1.00 score 504 downloads

CopulaGAMM - Copula-Based Mixed Regression Models

Estimation of 2-level factor copula-based regression models for clustered data where the response variable can be either discrete or continuous.

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1.00 score 639 downloads

phylopairs - Comparative Analyses of Lineage-Pair Traits

Facilitates the testing of causal relationships among lineage-pair traits in a phylogenetically informed context. Lineage-pair traits are characters that are defined for pairs of lineages instead of individual taxa. Examples include the strength of reproductive isolation, range overlap, competition coefficient, diet niche similarity, and relative hybrid fitness. Users supply a lineage-pair dataset and a phylogeny. 'phylopairs' calculates a covariance matrix for the pairwise-defined data and provides built-in models to test for relationships among variables while taking this covariance into account. Bayesian sampling is run through built-in 'Stan' programs via the 'rstan' package. The various models and methods that this package makes available are described in Anderson et al. (In Review), Coyne and Orr (1989) <doi:10.1111/j.1558-5646.1989.tb04233.x>, Fitzpatrick (2002) <doi:10.1111/j.0014-3820.2002.tb00860.x>, and Castillo (2007) <doi:10.1002/ece3.3093>.

featForge - Automated Feature Engineering for Credit Scoring

Automated feature engineering functions tailored for credit scoring. It includes utilities for extracting structured features from timestamps, IP addresses, and email addresses, enabling enhanced predictive modeling for financial risk assessment.

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1.00 score 1 scripts 123 downloads

cobenrich - Using Multiple Continuous Biomarkers for Patient Enrichment in Two-Stage Clinical Designs

Enrichment strategies play a critical role in modern clinical trial design, especially as precision medicine advances the focus on patient-specific efficacy. Recent developments in enrichment design have introduced biomarker randomness and accounted for the correlation structure between treatment effect and biomarker, resulting in a two-stage threshold enrichment design. We propose novel two-stage enrichment designs capable of handling two or more continuous biomarkers. See Zhang, F. and Gou, J. (2025). Using multiple biomarkers for patient enrichment in two-stage clinical designs. Technical Report.

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1.00 score 139 downloads

qlifetable - Managing and Building of Quarterly Life Tables

Manages, builds and computes statistics and datasets for the construction of quarterly (sub-annual) life tables by exploiting micro-data from either a general or an insured population. References: Pavía and Lledó (2022) <doi:10.1111/rssa.12769>. Pavía and Lledó (2023) <doi:10.1017/asb.2023.16>. Pavía and Lledó (2025) <doi:10.1371/journal.pone.0315937>. Acknowledgements: The authors wish to thank Conselleria de Educación, Universidades y Empleo, Generalitat Valenciana (grants AICO/2021/257; CIAICO/2024/031), Ministerio de Ciencia e Innovación (grant PID2021-128228NB-I00) and Fundación Mapfre (grant 'Modelización espacial e intra-anual de la mortalidad en España. Una herramienta automática para el calculo de productos de vida') for supporting this research.

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1.00 score 239 downloads

rjaf - Regularized Joint Assignment Forest with Treatment Arm Clustering

Personalized assignment to one of many treatment arms via regularized and clustered joint assignment forests as described in Ladhania, Spiess, Ungar, and Wu (2023) <doi:10.48550/arXiv.2311.00577>. The algorithm pools information across treatment arms: it considers a regularized forest-based assignment algorithm based on greedy recursive partitioning that shrinks effect estimates across arms; and it incorporates a clustering scheme that combines treatment arms with consistently similar outcomes.

Implements the new algorithm for fast computation of M-scatter matrices using a partial Newton-Raphson procedure for several estimators. The algorithm is described in Duembgen, Nordhausen and Schuhmacher (2016) <doi:10.1016/j.jmva.2015.11.009>.

A big data version for fitting cumulative probability models using the orm() function from the 'rms' package. See Liu et al. (2017) <DOI:10.1002/sim.7433> for details.

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1.00 score 200 downloads

RcppDPR - 'Rcpp' Implementation of Dirichlet Process Regression

'Rcpp' reimplementation of the the Bayesian non-parametric Dirichlet Process Regression model for penalized regression first published in Zeng and Zhou (2017) <doi:10.1038/s41467-017-00470-2>. A full Bayesian version is implemented with Gibbs sampling, as well as a faster but less accurate variational Bayes approximation.

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openblasgslcpp

1.00 score 173 downloads

StatRec - A Statistical Method for Multi-Item Rating and Recommendation Problems

Implements the methodological developments found in Hermes (2025) <doi:10.48550/arXiv.2503.02786>, and allows for the statistical modeling of data consisting of multiple users that provide an ordinal rating for one or multiple items.

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openblascppopenmp

1.00 score 152 downloads

Ropj - Import Origin(R) Project Files

Read the data from Origin(R) project files ('*.opj') <https://www.originlab.com/doc/User-Guide/Origin-File-Types>. No write support is planned.

fbati - Gene by Environment Interaction and Conditional Gene Tests for Nuclear Families

Does family-based gene by environment interaction tests, joint gene, gene-environment interaction test, and a test of a set of genes conditional on another set of genes.

rsides - SIDES-Based Subgroup Search Algorithms

R implementation of SIDES-based subgroup search algorithms (Lipkovich et al. (2017) <doi:10.1002/sim.7064>).

Simultaneous/joint diagonalization of local autocovariance matrices to estimate spatio-temporally uncorrelated random fields.

Provides predictive accuracy tools to evaluate time-to-event survival models. This includes calculating the concordance probability estimate that incorporates the follow-up time for a particular study developed by Devlin, Gonen, Heller (2020)<doi:10.1007/s10985-020-09503-3>. It also evaluates the concordance probability estimate for nested Cox proportional hazards models using a projection-based approach by Heller and Devlin (under review).

Bayesian power/type I error calculation and model fitting using the power prior and the normalized power prior for proportional hazards models with piecewise constant hazard. The methodology and examples of applying the package are detailed in <doi:10.48550/arXiv.2404.05118>. The Bayesian clinical trial design methodology is described in Chen et al. (2011) <doi:10.1111/j.1541-0420.2011.01561.x>, and Psioda and Ibrahim (2019) <doi:10.1093/biostatistics/kxy009>. The proportional hazards model with piecewise constant hazard is detailed in Ibrahim et al. (2001) <doi:10.1007/978-1-4757-3447-8>.

1.00 score 145 downloads

fastliu - Fast Functions for Liu Regression with Regularization Parameter and Statistics

Efficient computation of the Liu regression coefficient paths, Liu-related statistics and information criteria for a grid of the regularization parameter. The computations are based on the 'C++' library 'Armadillo' through the 'R' package 'Rcpp'.

Performing multiple-class cluster correspondence analysis(MCCCA). The main functions are create.MCCCAdata() to create a list to be applied to MCCCA, MCCCA() to apply MCCCA, and plot.mccca() for visualizing MCCCA result. Methods used in the package refers to Mariko Takagishi and Michel van de Velden (2022)<doi:10.1080/10618600.2022.2035737>.

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openblascppopenmp

1.00 score 185 downloads

gldrm - Generalized Linear Density Ratio Models

Fits a generalized linear density ratio model (GLDRM). A GLDRM is a semiparametric generalized linear model. In contrast to a GLM, which assumes a particular exponential family distribution, the GLDRM uses a semiparametric likelihood to estimate the reference distribution. The reference distribution may be any discrete, continuous, or mixed exponential family distribution. The model parameters, which include both the regression coefficients and the cdf of the unspecified reference distribution, are estimated by maximizing a semiparametric likelihood. Regression coefficients are estimated with no loss of efficiency, i.e. the asymptotic variance is the same as if the true exponential family distribution were known. Huang (2014) <doi:10.1080/01621459.2013.824892>. Huang and Rathouz (2012) <doi:10.1093/biomet/asr075>. Rathouz and Gao (2008) <doi:10.1093/biostatistics/kxn030>.

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1.00 score 9 scripts 155 downloads

bpAcc - Blood Pressure Device Accuracy Evaluation: Statistical Considerations

A comprehensive statistical analysis of the accuracy of blood pressure devices based on the method of AAMI/ANSI SP10 standards developed by the AAMI Sphygmomanometer Committee for indirect measurement of blood pressure, incorporated into IS0 81060-2. The 'bpAcc' package gives the exact probability 'of accepting a device D' derived from the join distribution of the sample standard deviation and a non-linear transformation of the sample mean for a specified sample size introduced by Chandel et al. (2023) and by the Association for the Advancement of Medical Instrumentation (2003, ISBN:1-57020-183-8).

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1.00 score 292 downloads

A common misconception is that the Hochberg procedure comes up with adequate overall type I error control when test statistics are positively correlated. However, unless the test statistics follow some standard distributions, the Hochberg procedure requires a more stringent positive dependence assumption, beyond mere positive correlation, to ensure valid overall type I error control. To fill this gap, we formulate statistical tests grounded in rank correlation coefficients to validate fulfillment of the positive dependence through stochastic ordering (PDS) condition. See Gou, J., Wu, K. and Chen, O. Y. (2024). Rank correlation coefficient based tests on positive dependence through stochastic ordering with application in cancer studies, Technical Report.

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1.00 score 132 downloads

LiftTest - A Bootstrap Proportion Test for Brand Lift Testing

A bootstrap proportion test for Brand Lift Testing to quantify the effectiveness of online advertising. Methods of the bootstrap proportion test are presented in Liu, Yu, Mao, Wu, Dyer (2023) <doi:10.1145/3583780.3615021>.

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1.00 score 167 downloads

EVchargcost - Computes and Plot the Optimal Charging Strategy for Electric Vehicles

The purpose of this library is to compute the optimal charging cost function for a electric vehicle (EV). It is well known that the charging function of a EV is a concave function that can be approximated by a piece-wise linear function, so bigger the state of charge, slower the charging process is. Moreover, the other important function is the one that gives the electricity price. This function is usually step-wise, since depending on the time of the day, the price of the electricity is different. Then, the problem of charging an EV to a certain state of charge is not trivial. This library implements an algorithm to compute the optimal charging cost function, that is, it plots for a given state of charge r (between 0 and 1) the minimum cost we need to pay in order to charge the EV to that state of charge r. The details of the algorithm are described in González-Rodríguez et at (2023) <https://inria.hal.science/hal-04362876v1>.

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1.00 score 114 downloads

ADER - Data Analysis in Ecology

Data sets used in Cayuela and De la Cruz (2022, ISBN:978-84-8476-833-3).

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1.00 score 3 scripts 327 downloads

longclust - Model-Based Clustering and Classification for Longitudinal Data

Clustering or classification of longitudinal data based on a mixture of multivariate t or Gaussian distributions with a Cholesky-decomposed covariance structure. Details in McNicholas and Murphy (2010) <doi:10.1002/cjs.10047> and McNicholas and Subedi (2012) <doi:10.1016/j.jspi.2011.11.026>.

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openblas

1.00 score 1 stars 5 scripts 153 downloads

icensBKL - Accompanion to the Book on Interval Censoring by Bogaerts, Komarek, and Lesaffre

Contains datasets and several smaller functions suitable for analysis of interval-censored data. The package complements the book Bogaerts, Komárek and Lesaffre (2017, ISBN: 978-1-4200-7747-6) "Survival Analysis with Interval-Censored Data: A Practical Approach" <https://www.routledge.com/Survival-Analysis-with-Interval-Censored-Data-A-Practical-Approach-with/Bogaerts-Komarek-Lesaffre/p/book/9781420077476>. Full R code related to the examples presented in the book can be found at <https://ibiostat.be/online-resources/icbook/supplemental>. Packages mentioned in the "Suggests" section are used in those examples.

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1.00 score 1 stars 3 scripts 244 downloads

THREC - Tree Height Response Calibration for Swedish Forests

A tool that allows users to estimate tree height in the long-term forest experiments in Sweden. It utilizes the multilevel nonlinear mixed-effect height models developed for the forest experiments and consists of four functions for the main species, other conifer species, and other broadleaves. Each function within the system returns a data frame that includes the input data and the estimated heights for any missing values. Ogana et al. (2023) <doi:10.1016/j.foreco.2023.120843>\n Arias-Rodil et al. (2015) <doi:10.1371/JOURNAL.PONE.0143521>.

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1.00 score 1 scripts 576 downloads

nice - Get or Set UNIX Niceness

Get or set UNIX priority (niceness) of running R process.

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1.00 score 4 scripts 64 downloads

InterfaceqPCR - GUI to Analyse qPCR Results after PMA Treatment or not

Graphical User Interface allowing to determine the concentration in the sample in CFU per mL or in number of copies per mL provided to qPCR results after with or without PMA treatment. This package is simply to use because no knowledge in R commands is necessary. A graphic represents the standard curve, and a table containing the result for each sample is created.

kcpRS - Kernel Change Point Detection on the Running Statistics

The running statistics of interest is first extracted using a time window which is slid across the time series, and in each window, the running statistics value is computed. KCP (Kernel Change Point) detection proposed by Arlot et al. (2012) <arXiv:1202.3878> is then implemented to flag the change points on the running statistics (Cabrieto et al., 2018, <doi:10.1016/j.ins.2018.03.010>). Change points are located by minimizing a variance criterion based on the pairwise similarities between running statistics which are computed via the Gaussian kernel. KCP can locate change points for a given k number of change points. To determine the optimal k, the KCP permutation test is first carried out by comparing the variance of the running statistics extracted from the original data to that of permuted data. If this test is significant, then there is sufficient evidence for at least one change point in the data. Model selection is then used to determine the optimal k>0.

Classical Boson Sampling using the algorithm of Clifford and Clifford (2017) <arXiv:1706.01260>. Also provides functions for generating random unitary matrices, evaluation of matrix permanents (both real and complex) and evaluation of complex permanent minors.

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cpp

1.00 score 3 scripts 239 downloads

KnowBR - Discriminating Well Surveyed Spatial Units from Exhaustive Biodiversity Databases

It uses species accumulation curves and diverse estimators to assess, at the same time, the levels of survey coverage in multiple geographic cells of a size defined by the user or polygons. It also enables the geographical depiction of observed species richness, survey effort and completeness values including a background with administrative areas.

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1.00 score 8 scripts 327 downloads

GGRidge - Graphical Group Ridge

The Graphical Group Ridge 'GGRidge' package package classifies ridge regression predictors in disjoint groups of conditionally correlated variables and derives different penalties (shrinkage parameters) for these groups of predictors. It combines the ridge regression method with the graphical model for high-dimensional data (i.e. the number of predictors exceeds the number of cases) or ill-conditioned data (e.g. in the presence of multicollinearity among predictors). The package reduces the mean square errors and the extent of over-shrinking of predictors as compared to the ridge method.Aldahmani, S. and Zoubeidi, T. (2020) <DOI:10.1080/00949655.2020.1803320>.

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1.00 score 3 scripts 758 downloads

viking - State-Space Models Inference by Kalman or Viking

Inference methods for state-space models, relying on the Kalman Filter or on Viking (Variational Bayesian VarIance tracKING). See J. de Vilmarest (2022) <https://theses.hal.science/tel-03716104/>.

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1.00 score 2 scripts 184 downloads

REPPlabShiny - 'REPPlab' via a Shiny Application

Performs exploratory projection pursuit via 'REPPlab' (Daniel Fischer, Alain Berro, Klaus Nordhausen & Anne Ruiz-Gazen (2019) <doi:10.1080/03610918.2019.1626880>) using a Shiny app.

SampleSizeProportions - Calculating Sample Size Requirements when Estimating the Difference Between Two Binomial Proportions

Sample size requirements calculation using three different Bayesian criteria in the context of designing an experiment to estimate the difference between two binomial proportions. Functions for calculation of required sample sizes for the Average Length Criterion, the Average Coverage Criterion and the Worst Outcome Criterion in the context of binomial observations are provided. In all cases, estimation of the difference between two binomial proportions is considered. Functions for both the fully Bayesian and the mixed Bayesian/likelihood approaches are provided. For reference see Joseph L., du Berger R. and Bélisle P. (1997) <doi:10.1002/(sici)1097-0258(19970415)16:7%3C769::aid-sim495%3E3.0.co;2-v>.

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1.00 score 10 scripts 178 downloads

kerTests - Generalized Kernel Two-Sample Tests

New kernel-based test and fast tests for testing whether two samples are from the same distribution. They work well particularly for high-dimensional data. Song, H. and Chen, H. (2023) <arXiv:2011.06127>.

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1.00 score 9 scripts 200 downloads

kerSeg - New Kernel-Based Change-Point Detection

New kernel-based test and fast tests for detecting change-points or changed-intervals where the distributions abruptly change. They work well particularly for high-dimensional data. Song, H. and Chen, H. (2022) <arXiv:2206.01853>.

Performs dose assignment and trial simulation for the FBCRM (Fully Bayesian Continual Reassessment Method) and MFBCRM (Mixture Fully Bayesian Continual Reassessment Method) phase I clinical trial designs. These trial designs extend the Continual Reassessment Method (CRM) and Bayesian Model Averaging Continual Reassessment Method (BMA-CRM) by allowing the prior toxicity skeleton itself to be random, with posterior distributions obtained from Markov Chain Monte Carlo. On average, the FBCRM and MFBCRM methods outperformed the CRM and BMA-CRM methods in terms of selecting an optimal dose level across thousands of randomly generated simulation scenarios. Details on the methods and results of this simulation study are available on request, and the manuscript is currently under review.

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cpp

1.00 score 25 downloads

sAIC - Akaike Information Criterion for Sparse Estimation

Computes the Akaike information criterion for the generalized linear models (logistic regression, Poisson regression, and Gaussian graphical models) estimated by the lasso.

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1.00 score 2 scripts 154 downloads

gllm - Generalised log-Linear Model

Routines for log-linear models of incomplete contingency tables, including some latent class models, via EM and Fisher scoring approaches. Allows bootstrapping. See Espeland and Hui (1987) <doi:10.2307/2531553> for general approach.

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1.00 score 8 scripts 248 downloads

spcr - Sparse Principal Component Regression

The sparse principal component regression is computed. The regularization parameters are optimized by cross-validation.

An implementation of a new Gini covariance and correlation to measure dependence between a categorical and numerical variables. Dang, X., Nguyen, D., Chen, Y. and Zhang, J., (2018) <arXiv:1809.09793>.

These are two-sample tests for categorical data utilizing similarity information among the categories. They are useful when there is underlying structure on the categories.

To make the semiparametric transformation models easier to apply in real studies, we introduce this R package, in which the MLE in transformation models via an EM algorithm proposed by Zeng D, Lin DY(2007) <doi:10.1111/j.1369-7412.2007.00606.x> and adaptive lasso method in transformation models proposed by Liu XX, Zeng D(2013) <doi:10.1093/biomet/ast029> are implemented. C++ functions are used to compute complex loops. The coefficient vector and cumulative baseline hazard function can be estimated, along with the corresponding standard errors and P values.

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cpp

1.00 score 223 downloads

CLONETv2 - Clonality Estimates in Tumor

Analyze data from next-generation sequencing experiments on genomic samples. 'CLONETv2' offers a set of functions to compute allele specific copy number and clonality from segmented data and SNPs position pileup. The package has also calculated the clonality of single nucleotide variants given read counts at mutated positions. The package has been developed at the laboratory of Computational and Functional Oncology, Department of CIBIO, University of Trento (Italy), under the supervision of prof Francesca Demichelis. References: Prandi et al. (2014) <doi:10.1186/s13059-014-0439-6>; Carreira et al. (2014) <doi:10.1126/scitranslmed.3009448>; Romanel et al. (2015) <doi:10.1126/scitranslmed.aac9511>.

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1.00 score 5 scripts 298 downloads

CorrectedFDR - Correcting False Discovery Rates

There are many estimators of false discovery rate. In this package we compute the Nonlocal False Discovery Rate (NFDR) and the estimators of local false discovery rate: Corrected False discovery Rate (CFDR), Re-ranked False Discovery rate (RFDR) and the blended estimator. Bickel, D.R., Rahal, A. (2019) <https://tinyurl.com/kkdc9rk8>.

1.00 score 144 downloads

MABOUST - Multi-Armed Bayesian Ordinal Utility-Based Sequential Trial

Conducts and simulates the MABOUST design, including making interim decisions to stop a treatment for inferiority or stop the trial early for superiority or equivalency.

RobustBayesianCopas - Robust Bayesian Copas Selection Model

Fits the robust Bayesian Copas (RBC) selection model of Bai et al. (2020) <arXiv:2005.02930> for correcting and quantifying publication bias in univariate meta-analysis. Also fits standard random effects meta-analysis and the Copas-like selection model of Ning et al. (2017) <doi:10.1093/biostatistics/kxx004>.

Simulating and conducting four phase 12 clinical trials with correlated binary bivariate outcomes described. Uses the 'Efftox' (efficacy and toxicity tradeoff, <https://biostatistics.mdanderson.org/SoftwareDownload/SingleSoftware/Index/2>) and SPSO (Semi-Parametric Stochastic Ordering) models with Utility and Desirability based objective functions for dose finding.

Optimization of any Black-Box/Non-Convex Function on Hyper-Rectangular Parameter Space. It uses a Variation of Pattern Search Technique. Described in the paper : Das (2016) <arXiv:1604.08616> .

Testing and inference for regression models using residual randomization methods. The basis of inference is an invariance assumption on the regression errors, e.g., clustered errors, or doubly-clustered errors.

An efficient implementation of SCCI using 'Rcpp'. SCCI is short for the Stochastic Complexity-based Conditional Independence criterium (Marx and Vreeken, 2019). SCCI is an asymptotically unbiased and L2 consistent estimator of (conditional) mutual information for discrete data.

Efficient algorithms for fitting regularization paths for linear or logistic regression models penalized by LEP.

Semblance - A Data-Driven Similarity Kernel on Probability Spaces

We present a rank-based Mercer kernel to compute a pair-wise similarity metric corresponding to informative representation of data. We tailor the development of a kernel to encode our prior knowledge about the data distribution over a probability space. The philosophical concept behind our construction is that objects whose feature values fall on the extreme of that feature’s probability mass distribution are more similar to each other, than objects whose feature values lie closer to the mean. Semblance emphasizes features whose values lie far away from the mean of their probability distribution. The kernel relies on properties empirically determined from the data and does not assume an underlying distribution. The use of feature ranks on a probability space ensures that Semblance is computational efficacious, robust to outliers, and statistically stable, thus making it widely applicable algorithm for pattern analysis. The output from the kernel is a square, symmetric matrix that gives proximity values between pairs of observations.

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1.00 score 2 scripts 55 downloads

bspmma - Bayesian Semiparametric Models for Meta-Analysis

The main functions carry out Gibbs' sampler routines for nonparametric and semiparametric Bayesian models for random effects meta-analysis.

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1.00 score 9 scripts 39 downloads

QHOT - QTL Hotspot Detection

This function produces both the numerical and graphical summaries of the QTL hotspot detection in the genomes that are available on the worldwide web including the flanking markers of QTLs.

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1.00 score 3 scripts 110 downloads

bwd - Backward Procedure for Change-Point Detection

Implements a backward procedure for single and multiple change point detection proposed by Shin et al. <arXiv:1812.10107>. The backward approach is particularly useful to detect short and sparse signals which is common in copy number variation (CNV) detection.

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1.00 score 2 scripts 155 downloads

mmsample - Multivariate Matched Sampling

Subset a control group to match an intervention group on a set of features using multivariate matching and propensity score calipers. Based on methods in Rosenbaum and Rubin (1985).