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

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 |

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'. |