This package is considered a duplicate. The official version of this package is found at:https://papgeo.r-universe.dev/BNSP

Package: BNSP 2.2.3

Georgios Papageorgiou

BNSP: Bayesian Non- And Semi-Parametric Model Fitting

MCMC algorithms & processing functions for: 1. single response multiple regression, see Papageorgiou, G. (2018) <doi:10.32614/RJ-2018-069>, 2. multivariate response multiple regression, with nonparametric models for the means, the variances and the correlation matrix, with variable selection, see Papageorgiou, G. and Marshall, B. C. (2020) <doi:10.1080/10618600.2020.1739534>, 3. joint mean-covariance models for multivariate responses, see Papageorgiou, G. (2022) <doi:10.1002/sim.9376>, and 4.Dirichlet process mixtures, see Papageorgiou, G. (2019) <doi:10.1111/anzs.12273>.

Authors:Georgios Papageorgiou

BNSP_2.2.3.tar.gz
BNSP_2.2.3.tar.gz(r-4.5-noble)BNSP_2.2.3.tar.gz(r-4.4-noble)
BNSP_2.2.3.tgz(r-4.4-emscripten)BNSP_2.2.3.tgz(r-4.3-emscripten)
BNSP.pdf |BNSP.html✨
BNSP/json (API)

# Install 'BNSP' in R:

install.packages('BNSP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

gsl– GNU Scientific Library (GSL)

Datasets:

ami - Amitriptyline dataset from Johnson and Wichern
simD - Simulated dataset
simD2 - Simulated dataset

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 511 downloads 14 exports 67 dependencies

Last updated 2 years agofrom:413e0a4202. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 31 2024
R-4.5-linux-x86_64	OK	Oct 31 2024

Exports:chol clustering continue dpmj histCorr lmrm mvrm mvrm2mcmc plotCorr s sinusoid sm te ti

Dependencies:base64enc bslib cachem cli coda colorspace combinat corrplot cpp11 crosstalk cubature digest evaluate fansi farver fastmap fontawesome Formula fs ggplot2 glue gridExtra gtable highr htmltools htmlwidgets igraph isoband jquerylib jsonlite knitr label.switching labeling lattice lazyeval lifecycle lpSolve magrittr MASS Matrix memoise mgcv mime misc3d munsell nlme pillar pkgconfig plot3D plyr R6 rappdirs RColorBrewer Rcpp rlang rmarkdown sass scales threejs tibble tinytex utf8 vctrs viridisLite withr xfun yaml

Help page	Topics
Bayesian non- and semi-parametric model fitting	BNSP-package BNSP
Amitriptyline dataset from Johnson and Wichern	ami
The Cholesky and modified Cholesky decompositions	chol
Computes the similarity matrix	clustering
Continues the sampler from where it stopped	continue
Dirichlet process mixtures of joint models	dpmj
Creates plots of correlation matrices	histCorr
Bayesian semiparametric modelling of covariance matrices for multivariate longitudinal data	lmrm
Bayesian semiparametric analysis of multivariate continuous responses, with variable selection	mvrm
Convert posterior samples from function 'mvrm' into an object of class `mcmc'	mvrm2mcmc
Creates plots of terms in the mean and/or variance models	plot.mvrm
Creates plots of the correlation matrices	plotCorr
Model predictions	predict.mvrm
Prints an mvrm fit	print.mvrm
mgcv constructor 's'	s
Simulated dataset	simD
Simulated dataset	simD2
Sinusoid terms in mvrm formulae	sinusoid
Smooth terms in mvrm formulae	sm
Summary of an mvrm fit	summary.mvrm
mgcv constructor 'te'	te
mgcv constructor 'ti'	ti

Package: BNSP 2.2.3

BNSP: Bayesian Non- And Semi-Parametric Model Fitting

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