Package: stan4bart 0.0-11

stan4bart: Bayesian Additive Regression Trees with Stan-Sampled Parametric Extensions

Fits semiparametric linear and multilevel models with non-parametric additive Bayesian additive regression tree (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) components and Stan (Stan Development Team (2021) <https://mc-stan.org/>) sampled parametric ones. Multilevel models can be expressed using 'lme4' syntax (Bates, Maechler, Bolker, and Walker (2015) <doi:10.18637/jss.v067.i01>).

Authors:Vincent Dorie [aut, cre], Ben Goodrich [ctb], Jonah Gabry [ctb], Imad Ali [ctb], Sam Brilleman [ctb], Paul-Christian Burkner [ctb], Joshua Pritikin [ctb], Andrew Gelman [ctb], Bob Carpenter [ctb], Matt Hoffman [ctb], Daniel Lee [ctb], Michael Betancourt [ctb], Marcus Brubaker [ctb], Jiqiang Guo [ctb], Peter Li [ctb], Allen Riddell [ctb], Marco Inacio [ctb], Mitzi Morris [ctb], Jeffrey Arnold [ctb], Rob Goedman [ctb], Brian Lau [ctb], Rob Trangucci [ctb], Alp Kucukelbir [ctb], Robert Grant [ctb], Dustin Tran [ctb], Michael Malecki [ctb], Yuanjun Gao [ctb], Trustees of Columbia University [cph], Lawrence Livermore National Security [cph], The Regents of the University of California [cph], Southern Methodist University [cph], Douglas Bates [ctb], Martin Maechler [ctb], Ben Bolker [ctb], Steve Walker [ctb], Armon Dadgar [ctb], Bothner Per [ctb], Elliston Ben [ctb], Free Software Foundation [cph], Guido U Draheim [ctb], Maarten Bosmans [ctb], Christophe Tournayre [ctb], Michael Petch [ctb], Rafael de Lucena Valle [ctb], Steven G. Johnson [ctb], Matteo Frigo [ctb], Scott Pakin [ctb]

stan4bart_0.0-11.tar.gz
stan4bart_0.0-11.zip(r-4.7)stan4bart_0.0-11.zip(r-4.6)stan4bart_0.0-11.zip(r-4.5)
stan4bart_0.0-11.tgz(r-4.6-x86_64)stan4bart_0.0-11.tgz(r-4.6-arm64)stan4bart_0.0-11.tgz(r-4.5-x86_64)stan4bart_0.0-11.tgz(r-4.5-arm64)
stan4bart_0.0-11.tar.gz(r-4.7-arm64)stan4bart_0.0-11.tar.gz(r-4.7-x86_64)stan4bart_0.0-11.tar.gz(r-4.6-arm64)stan4bart_0.0-11.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
stan4bart/json (API)
NEWS

# Install 'stan4bart' in R:
install.packages('stan4bart', repos = c('https://vdorie.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/vdorie/stan4bart/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

bartbayesianstancpp

5.23 score 47 stars 36 scripts 601 downloads 1 exports 7 dependencies

Last updated from:94f6d1fda1. Checks:4 WARNING, 4 OK, 5 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64WARNING235
linux-devel-x86_64WARNING214
source / vignettesOK246
linux-release-arm64WARNING220
linux-release-x86_64WARNING256
macos-release-arm64FAIL82
macos-release-x86_64FAIL317
macos-oldrel-arm64OK138
macos-oldrel-x86_64OK408
windows-develFAIL135
windows-releaseFAIL98
windows-oldrelOK273
wasm-releaseFAIL136

Exports:stan4bart

Dependencies:BHdbartslatticeMatrixRcppRcppEigenRcppParallel

Readme and manuals

Help Manual

Help pageTopics
Semiparametric Models Using Stan and BARTstan4bart
Generic Functions for stan4bart Model Fitsextract extract.stan4bartFit fitted.stan4bartFit predict.stan4bartFit stan4bart-generics