Bayesian Additive Regression Trees
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
Logit BART for dichotomous outcomes with Logistic latents and parallel...
Probit BART for dichotomous outcomes with Normal latents and parallel ...
Predicting new observations with a previously fitted BART model
Global SE variable selection for BART with parallel computation
BART for continuous outcomes with parallel computation
Probit BART for dichotomous outcomes with Normal latents
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
Predicting new observations with a previously fitted BART model
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
BART for dichotomous outcomes with parallel computation and stratified...
Testing truncated Gamma sampling
Testing truncated Normal sampling
AFT BART for time-to-event outcomes
Bayesian Additive Regression Trees
Create a matrix out of a vector or data.frame
Generates Class Indicator Matrix from a Factor
BART for competing risks
Data construction for competing risks with BART
BART for competing risks
Testing truncated Normal sampling
Generalized BART for continuous and binary outcomes
Geweke's convergence diagnostic
Logit BART for dichotomous outcomes with Logistic latents
Multinomial BART for categorical outcomes with fewer categories
Multinomial BART for categorical outcomes with more categories
Detecting OpenMP
Estimate spectral density at zero
Stepwise Variable Selection Procedure for survreg
Perform stratified random sampling to balance outcomes
Survival analysis with BART
Data construction for survival analysis with BART
BART for continuous outcomes
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>.