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

Package: dlmtree 1.0.0

Daniel Mork

dlmtree: Bayesian Treed Distributed Lag Models

Estimation of distributed lag models (DLMs) based on a Bayesian additive regression trees framework. Includes several extensions of DLMs: treed DLMs and distributed lag mixture models (Mork and Wilson, 2023) <doi:10.1111/biom.13568>; treed distributed lag nonlinear models (Mork and Wilson, 2022) <doi:10.1093/biostatistics/kxaa051>; heterogeneous DLMs (Mork, et. al., 2024) <doi:10.1080/01621459.2023.2258595>; monotone DLMs (Mork and Wilson, 2024) <doi:10.1214/23-BA1412>. The package also includes visualization tools and a 'shiny' interface to help interpret results.

Authors:Daniel Mork [aut, cre, cph], Seongwon Im [aut], Ander Wilson [aut]

dlmtree_1.0.0.tar.gz
dlmtree_1.0.0.tar.gz(r-4.5-noble)dlmtree_1.0.0.tar.gz(r-4.4-noble)
dlmtree_1.0.0.tgz(r-4.4-emscripten)dlmtree_1.0.0.tgz(r-4.3-emscripten)
dlmtree.pdf |dlmtree.html✨
dlmtree/json (API)
NEWS

# Install 'dlmtree' in R:

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

Bug tracker:https://github.com/danielmork/dlmtree/issues

Pkgdown site:https://danielmork.github.io

Uses libs:

c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

coExp - Randomly sampled exposure from Colorado counties
exposureCov - Exposure covariance structure
pm25Exposures - PM2.5 Exposure data
zinbCo - Time-series exposure data for ZINB simulated data

fortran cpp openmp

1.88 score 15 scripts 531 downloads 63 exports 62 dependencies

Last updated 7 months agofrom:05d9aef9e0. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 28 2024
R-4.5-linux-x86_64	OK	Dec 28 2024

Exports:adj_coexposure combine.models combine.models.tdlmm cppIntersection dlmEst dlmtree dlmtreeGPFixedGaussian dlmtreeGPGaussian dlmtreeHDLMGaussian dlmtreeHDLMMGaussian dlmtreeTDLM_cpp dlmtreeTDLMFixedGaussian dlmtreeTDLMNestedGaussian dlnmEst dlnmPLEst drawTree estDLM get_sbd_dlmtree mixEst monotdlnm_Cpp pip plot.summary.monotone plot.summary.tdlm plot.summary.tdlmm plot.summary.tdlnm ppRange predict.hdlm predict.hdlmm print.hdlm print.hdlmm print.monotone print.summary.hdlm print.summary.hdlmm print.summary.monotone print.summary.tdlm print.summary.tdlmm print.summary.tdlnm print.tdlm print.tdlmm print.tdlnm rcpp_pgdraw rtmvnorm ruleIdx scaleModelMatrix shiny shiny.hdlm shiny.hdlmm sim.hdlmm sim.tdlmm sim.tdlnm splitPIP splitpoints summary.hdlm summary.hdlmm summary.monotone summary.tdlm summary.tdlmm summary.tdlnm tdlmm tdlmm_Cpp tdlnm tdlnm_Cpp zeroToInfNormCDF

Dependencies:base64enc bslib cachem cli colorspace commonmark cpp11 crayon digest dplyr fansi farver fastmap fontawesome fs generics ggplot2 glue gtable htmltools httpuv isoband jquerylib jsonlite labeling later lattice lifecycle magrittr MASS Matrix memoise mgcv mime munsell nlme pillar pkgconfig promises purrr R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen rlang sass scales shiny shinythemes sourcetools stringi stringr tibble tidyr tidyselect utf8 vctrs viridisLite withr xtable

Help page	Topics
Adjusting for expected changes in co-exposure (TDLMM)	adj_coexposure
Randomly sampled exposure from Colorado counties	coExp
Combines information from DLMs of single exposure	combine.models
Combines information from DLMs of mixture exposures.	combine.models.tdlmm
fast set intersection tool assumes sorted vectors A and B	cppIntersection
Calculates the distributed lag effect with DLM matrix for linear models.	dlmEst
Fit tree structured distributed lag models	dlmtree
dlmtree model with fixed Gaussian process approach	dlmtreeGPFixedGaussian
dlmtree model with Gaussian process approach	dlmtreeGPGaussian
dlmtree model with shared HDLM approach	dlmtreeHDLMGaussian
dlmtree model with HDLMM approach	dlmtreeHDLMMGaussian
dlmtree model with nested HDLM approach	dlmtreeTDLM_cpp
dlmtree model with fixed Gaussian approach	dlmtreeTDLMFixedGaussian
dlmtree model with nested Gaussian approach	dlmtreeTDLMNestedGaussian
Calculates the distributed lag effect with DLM matrix for non-linear models.	dlnmEst
Calculates the distributed lag effect with DLM matrix for non-linear models.	dlnmPLEst
Draws a new tree structure	drawTree
Calculates subgroup-specific lag effects for heterogeneous models	estDLM
Exposure covariance structure	exposureCov
Download simulated data for dlmtree articles	get_sbd_dlmtree
Calculates the lagged interaction effects with MIX matrix for linear models.	mixEst
dlmtree model with monotone tdlnm approach	monotdlnm_Cpp
Calculates posterior inclusion probabilities (PIPs) for modifiers in HDLM & HDLMM	pip
Returns variety of plots for model summary of class 'monotone'	plot.summary.monotone
Plots a distributed lag function for model summary of 'tdlm'	plot.summary.tdlm
Plots DLMMs for model summary of class 'tdlmm'	plot.summary.tdlmm
Returns variety of plots for model summary of class 'tdlnm'	plot.summary.tdlnm
PM2.5 Exposure data	pm25Exposures
Makes a 'pretty' output of a group of numbers	ppRange
Calculates predicted response for HDLM	predict.hdlm
Calculates predicted response for HDLMM	predict.hdlmm
Print a hdlm Object	print.hdlm
Print a hdlmm Object	print.hdlmm
Print a monotone Object	print.monotone
Prints an overview with summary of model class 'hdlm'	print.summary.hdlm
Prints an overview with summary of model class 'hdlmm'	print.summary.hdlmm
Prints an overview with summary of model class 'monotone'	print.summary.monotone
Prints an overview with summary of model class 'tdlm'	print.summary.tdlm
Prints an overview with summary of model class 'tdlmm'	print.summary.tdlmm
Prints an overview with summary of model class 'tdlnm'	print.summary.tdlnm
Print a tdlm Object	print.tdlm
Print a tdlmm Object	print.tdlmm
Print a tdlnm Object	print.tdlnm
Multiple draw polya gamma latent variable for var c[i] with size b[i]	rcpp_pgdraw
Truncated multivariate normal sampler, mean mu, cov sigma, truncated (0, Inf)	rtmvnorm
Calculates the weights for each modifier rule	ruleIdx
Centers and scales a matrix	scaleModelMatrix
shiny	shiny
Executes a 'shiny' app for HDLM.	shiny.hdlm
Executes a 'shiny' app for HDLMM.	shiny.hdlmm
Creates simulated data for HDLM & HDLMM	sim.hdlmm
Creates simulated data for TDLM & TDLMM	sim.tdlmm
Creates simulated data for TDLNM	sim.tdlnm
Calculates the posterior inclusion probability (PIP).	splitPIP
Determines split points for continuous modifiers	splitpoints
Creates a summary object of class 'hdlm'	summary.hdlm
Creates a summary object of class 'hdlmm'	summary.hdlmm
Creates a summary object of class 'monotone'	summary.monotone
Creates a summary object of class 'tdlm'	summary.tdlm
Creates a summary object of class 'tdlmm'	summary.tdlmm
Creates a summary object of class 'tdlnm'	summary.tdlnm
Treed Distributed Lag Mixture Models (Deprecated)	tdlmm
dlmtree model with tdlmm approach	tdlmm_Cpp
Treed Distributed Lag Non-Linear Models (Deprecated)	tdlnm
dlmtree model with tdlnm approach	tdlnm_Cpp
Integrates (0,inf) over multivariate normal	zeroToInfNormCDF
Time-series exposure data for ZINB simulated data	zinbCo

Package: dlmtree 1.0.0

dlmtree: Bayesian Treed Distributed Lag Models

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)