Package: BART 2.9.10

BART: Bayesian Additive Regression Trees

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>.

Authors:Robert McCulloch [aut], Rodney Sparapani [aut, cre], Robert Gramacy [ctb], Matthew Pratola [ctb], Charles Spanbauer [ctb], Martyn Plummer [ctb], Nicky Best [ctb], Kate Cowles [ctb], Karen Vines [ctb]

BART_2.9.10.tar.gz
BART_2.9.10.zip(r-4.7)BART_2.9.10.zip(r-4.6)BART_2.9.10.zip(r-4.5)
BART_2.9.10.tgz(r-4.6-x86_64)BART_2.9.10.tgz(r-4.6-arm64)BART_2.9.10.tgz(r-4.5-x86_64)BART_2.9.10.tgz(r-4.5-arm64)
BART_2.9.10.tar.gz(r-4.7-arm64)BART_2.9.10.tar.gz(r-4.7-x86_64)BART_2.9.10.tar.gz(r-4.6-arm64)BART_2.9.10.tar.gz(r-4.6-x86_64)
BART_2.9.10.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
BART/json (API)

# Install 'BART' in R:

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

Uses libs:

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

Datasets:

ACTG175 - AIDS Clinical Trials Group Study 175
alligator - American alligator Food Choice
arq - NHANES 2009-2010 Arthritis Questionnaire
bladder - Bladder Cancer Recurrences
bladder1 - Bladder Cancer Recurrences
bladder2 - Bladder Cancer Recurrences
leukemia - Bone marrow transplantation for leukemia and multi-state models
lung - NCCTG Lung Cancer Data
transplant - Liver transplant waiting list
xdm20.test - A data set used in example of 'recur.bart'.
xdm20.train - A real data example for 'recur.bart'.
ydm20.test - A data set used in example of 'recur.bart'.
ydm20.train - A data set used in example of 'recur.bart'.

On CRAN:

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

cpp openmp

8.50 score 17 stars 18 packages 1.0k scripts 3.3k downloads 63 mentions 45 exports 5 dependencies

Last updated from:7da906e4db. Checks:11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	195
linux-devel-x86_64	NOTE	191
source / vignettes	OK	288
linux-release-arm64	NOTE	195
linux-release-x86_64	NOTE	181
macos-release-arm64	NOTE	185
macos-release-x86_64	NOTE	449
macos-oldrel-arm64	NOTE	180
macos-oldrel-x86_64	NOTE	317
windows-devel	NOTE	216
windows-release	NOTE	204
windows-oldrel	NOTE	181
wasm-release	OK	141

Exports:abart bartModelMatrix class.ind crisk.bart crisk.pre.bart crisk2.bart draw_lambda_i gbart gewekediag lbart mbart mbart2 mc.abart mc.cores.openmp mc.crisk.bart mc.crisk.pwbart mc.crisk2.bart mc.crisk2.pwbart mc.gbart mc.lbart mc.mbart mc.mbart2 mc.pbart mc.pwbart mc.recur.bart mc.recur.pwbart mc.surv.bart mc.surv.pwbart mc.wbart mc.wbart.gse pbart pwbart recur.bart recur.pre.bart recur.pwbart rs.pbart rtgamma rtnorm spectrum0ar srstepwise stratrs surv.bart surv.pre.bart surv.pwbart wbart

Dependencies:lattice Matrix nlme Rcpp survival

The BART R package

Rendered fromthe-BART-R-package.Rnwusingknitr::knitr

Last update: 2023-03-25
Started: 2019-03-28

Help page	Topics
Bayesian Additive Regression Trees	BART-package BART
AFT BART for time-to-event outcomes	abart mc.abart
AIDS Clinical Trials Group Study 175	ACTG175
American alligator Food Choice	alligator
NHANES 2009-2010 Arthritis Questionnaire	arq
Create a matrix out of a vector or data.frame	bartModelMatrix
Bladder Cancer Recurrences	bladder bladder1 bladder2
Generates Class Indicator Matrix from a Factor	class.ind
BART for competing risks	crisk.bart mc.crisk.bart
Data construction for competing risks with BART	crisk.pre.bart
BART for competing risks	crisk2.bart mc.crisk2.bart
Testing truncated Normal sampling	draw_lambda_i
Generalized BART for continuous and binary outcomes	gbart mc.gbart
Geweke's convergence diagnostic	gewekediag
Logit BART for dichotomous outcomes with Logistic latents	lbart
Bone marrow transplantation for leukemia and multi-state models	leukemia
NCCTG Lung Cancer Data	cancer lung
Multinomial BART for categorical outcomes with fewer categories	mbart mc.mbart
Multinomial BART for categorical outcomes with more categories	mbart2 mc.mbart2
Detecting OpenMP	mc.cores.openmp
Predicting new observations with a previously fitted BART model	mc.crisk.pwbart
Predicting new observations with a previously fitted BART model	mc.crisk2.pwbart
Logit BART for dichotomous outcomes with Logistic latents and parallel computation	mc.lbart
Probit BART for dichotomous outcomes with Normal latents and parallel computation	mc.pbart
Predicting new observations with a previously fitted BART model	mc.recur.pwbart mc.surv.pwbart recur.pwbart surv.pwbart
BART for continuous outcomes with parallel computation	mc.wbart
Global SE variable selection for BART with parallel computation	mc.wbart.gse
Probit BART for dichotomous outcomes with Normal latents	pbart
Predicting new observations with a previously fitted BART model	predict.crisk2bart
Predicting new observations with a previously fitted BART model	predict.criskbart
Predicting new observations with a previously fitted BART model	predict.lbart
Predicting new observations with a previously fitted BART model	predict.mbart predict.mbart2
Predicting new observations with a previously fitted BART model	predict.pbart
Predicting new observations with a previously fitted BART model	predict.recurbart
Predicting new observations with a previously fitted BART model	predict.survbart
Predicting new observations with a previously fitted BART model	predict.wbart
Predicting new observations with a previously fitted BART model	mc.pwbart pwbart
BART for recurrent events	mc.recur.bart recur.bart
Data construction for recurrent events with BART	recur.pre.bart
BART for dichotomous outcomes with parallel computation and stratified random sampling	rs.pbart
Testing truncated Gamma sampling	rtgamma
Testing truncated Normal sampling	rtnorm
Estimate spectral density at zero	spectrum0ar
Stepwise Variable Selection Procedure for survreg	srstepwise
Perform stratified random sampling to balance outcomes	stratrs
Survival analysis with BART	mc.surv.bart surv.bart
Data construction for survival analysis with BART	surv.pre.bart
Liver transplant waiting list	transplant
BART for continuous outcomes	wbart
A data set used in example of 'recur.bart'.	xdm20.test
A real data example for 'recur.bart'.	xdm20.train
A data set used in example of 'recur.bart'.	ydm20.test ydm20.train

Package: BART 2.9.10

BART: Bayesian Additive Regression Trees

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)