Package: dbarts 0.9-31

dbarts: Discrete Bayesian Additive Regression Trees Sampler

Fits Bayesian additive regression trees (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) while allowing the updating of predictors or response so that BART can be incorporated as a conditional model in a Gibbs/Metropolis-Hastings sampler. Also serves as a drop-in replacement for package 'BayesTree'.

Authors:Vincent Dorie [aut, cre], Hugh Chipman [aut], Robert McCulloch [aut], Armon Dadgar [ctb], R Core Team [ctb], 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], John Zaitseff [ctb], Todd Veldhuizen [ctb], Luc Maisonobe [ctb], Scott Pakin [ctb], Daniel Richard G. [ctb]

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dbarts.pdf |dbarts.html✨
dbarts/json (API)
NEWS

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

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

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

On CRAN:

Conda:

cpp

11.21 score 58 stars 14 packages 418 scripts 3.3k downloads 2 mentions 14 exports 0 dependencies

Last updated 5 hours agofrom:3bd53d6c96. Checks:12 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKApr 01 2025
R-4.5-win-x86_64OKApr 01 2025
R-4.5-mac-x86_64OKApr 01 2025
R-4.5-mac-aarch64OKApr 01 2025
R-4.5-linux-x86_64OKApr 01 2025
R-4.4-win-x86_64OKApr 01 2025
R-4.4-mac-x86_64OKApr 01 2025
R-4.4-mac-aarch64OKApr 01 2025
R-4.4-linux-x86_64OKApr 01 2025
R-4.3-win-x86_64OKApr 01 2025
R-4.3-mac-x86_64OKApr 01 2025
R-4.3-mac-aarch64OKApr 01 2025

Exports:bartbart2dbartsdbartsControldbartsDataextractguessNumCoresmakeindmakeModelMatrixFromDataFramemakeTestModelMatrixpd2bartpdbartrbart_vixbart

Dependencies:

Building a Gibbs Sampler with dbarts

Vincent Dorie

Rendered fromgibbs_sampler_mixture_model.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2020-12-21
Started: 2020-12-21

Working with dbarts Saved Trees

Vincent Dorie

Rendered fromworking_with_saved_trees.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2022-03-27
Started: 2022-01-24

Readme and manuals

Help Manual

Help pageTopics
Bayesian Additive Regression Treesbart bart2 extract extract.bart fitted.bart plot.bart predict.bart residuals.bart
Discrete Bayesian Additive Regression Trees Samplerdbarts
Discrete Bayesian Additive Regression Trees Sampler ControldbartsControl
Discrete Bayesian Additive Regression Trees Sampler DatadbartsData
Class "dbartsSampler" of Discrete Bayesian Additive Regression Trees SamplerdbartsSampler dbartsSampler-class \S4method{copy}{dbartsSampler} \S4method{plotTree}{dbartsSampler} \S4method{predict}{dbartsSampler} \S4method{printTrees}{dbartsSampler} \S4method{run}{dbartsSampler} \S4method{sampleNodeParametersFromPrior}{dbartsSampler} \S4method{sampleTreesFromPrior}{dbartsSampler} \S4method{setControl}{dbartsSampler} \S4method{setData}{dbartsSampler} \S4method{setModel}{dbartsSampler} \S4method{setOffset}{dbartsSampler} \S4method{setPredictor}{dbartsSampler} \S4method{setResponse}{dbartsSampler} \S4method{setSigma}{dbartsSampler} \S4method{setTestOffset}{dbartsSampler} \S4method{setTestPredictorAndOffset}{dbartsSampler} \S4method{setTestPredictor}{dbartsSampler} \S4method{show}{dbartsSampler} \S4method{startThreads}{dbartsSampler} \S4method{stopThreads}{dbartsSampler}
Guess Number of CoresguessNumCores
Make Model Matrix from Data Framemakeind makeModelMatrixFromDataFrame makeTestModelMatrix
Partial Dependence Plots for BARTpd2bart pdbart plot.pd2bart plot.pdbart
Bayesian Additive Regression Trees with Random Effectsextract.rbart fitted.rbart plot.rbart predict.rbart rbart_vi residuals.rbart
Crossvalidation For Bayesian Additive Regression Treesxbart