CRAN/E | BART

BART

Bayesian Additive Regression Trees

Installation

About

Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous, binary, categorical and time-to-event outcomes. For more information see Sparapani, Spanbauer and McCulloch doi:10.18637/jss.v097.i01.

Citation BART citation info

Key Metrics

Version 2.9.4
R ≥ 2.10
Published 2023-03-25 185 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks BART results

Downloads

Last 24 hours 0 -100%
Last 7 days 423 -8%
Last 30 days 1.735 -13%
Last 90 days 5.249 -23%
Last 365 days 27.227 +54%

Maintainer

Maintainer

Rodney Sparapani

rsparapa@mcw.edu

Authors

Robert McCulloch

aut

Rodney Sparapani

aut / cre

Charles Spanbauer

aut

Robert Gramacy

aut

Matthew Pratola

aut

Martyn Plummer

ctb

Nicky Best

ctb

Kate Cowles

ctb

Karen Vines

ctb

Material

NEWS
Reference manual
Package source

In Views

Bayesian
MachineLearning

Vignettes

The BART R package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

BART archive

Depends

R ≥ 2.10
nlme
nnet
survival

Imports

Rcpp ≥ 0.12.3
parallel
tools

Suggests

MASS
knitr
rmarkdown

LinkingTo

Rcpp

Reverse Depends

cjbart

Reverse Imports

borrowr
CIMTx
paths
riAFTBART
SAMTx

Reverse Suggests

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condvis2
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