Bayesian Additive Regression Trees

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Documentation for package ‘BART’ version 1.1

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BART-package Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous, binary and time-to-event outcomes.
BART Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous, binary and time-to-event outcomes.
bladder Bladder Cancer Recurrences
bladder1 Bladder Cancer Recurrences
bladder2 Bladder Cancer Recurrences
cancer NCCTG Lung Cancer Data
crisk.bart BART for competing risks
crisk.pre.bart Data construction for competing risks with BART
lung NCCTG Lung Cancer Data
mc.crisk.bart BART for competing risks
mc.crisk.pwbart Predicting new observations with a previously fitted BART model
mc.pbart BART for dichotomous outcomes with 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 BART for dichotomous outcomes
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
surv.bart Survival analysis with BART
surv.pre.bart Data construction for survival analysis with BART
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'.