# Bayesian Additive Regression Trees

## Documentation for package ‘BART’ version 2.9.9

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Code demos. Use demo() to run them.
- Package NEWS.

## Help Pages

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