NHANES 2009-2010 Arthritis Questionnaire
AIDS Clinical Trials Group Study 175
Data construction for competing risks with BART
AFT BART for time-to-event outcomes
BART for competing risks
Bladder Cancer Recurrences
Bayesian Additive Regression Trees
BART for competing risks
American alligator Food Choice
Create a matrix out of a vector or data.frame
Geweke's convergence diagnostic
Logit BART for dichotomous outcomes with Logistic latents
Testing truncated Normal sampling
Bone marrow transplantation for leukemia and multi-state models
NCCTG Lung Cancer Data
Generalized BART for continuous and binary outcomes
Detecting OpenMP
Predicting new observations with a previously fitted BART model
Multinomial BART for categorical outcomes with fewer categories
Multinomial BART for categorical outcomes with more categories
Predicting new observations with a previously fitted BART model
Probit BART for dichotomous outcomes with Normal latents
Logit BART for dichotomous outcomes with Logistic latents and parallel computation
Predicting new observations with a previously fitted BART model
BART for continuous outcomes with parallel computation
Predicting new observations with a previously fitted BART model
Global SE variable selection for BART with parallel computation
Probit BART for dichotomous outcomes with Normal latents and parallel computation
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
BART for recurrent events
Data construction for recurrent events with BART
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
BART for dichotomous outcomes with parallel computation and
stratified random sampling
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
Liver transplant waiting list
Predicting new observations with a previously fitted BART model
Survival analysis with BART
BART for continuous outcomes
Data construction for survival analysis with BART
Predicting new observations with a previously fitted BART model
Testing truncated Gamma sampling
A data set used in example of recur.bart.
Testing truncated Normal sampling
Estimate spectral density at zero
Stepwise Variable Selection Procedure for survreg
Perform stratified random sampling to balance outcomes
A data set used in example of recur.bart.
A real data example for recur.bart.