Man pages for BartMixVs
Variable Selection Using Bayesian Additive Regression Trees
| abc.vs | Variable selection with ABC Bayesian forest |
| BartMixVs-package | Varibale Selection Using Bayesian Additive Regression Trees |
| bartModelMatrix | Create a matrix out of a vector or data frame |
| checkerboard | Generate data for an example of Zhu, Zeng and Kosorok (2015) |
| friedman | Generate data for an example of Friedman (1991) |
| mc.abc.vs | Variable selection with ABC Bayesian forest (using parallel... |
| mc.backward.vs | Backward selection with two filters (using parallel... |
| mc.cores.openmp | Detecting OpenMP |
| mc.pbart | Probit BART for binary responses with parallel computation |
| mc.permute.vs | Permutation-based variable selection approach with parallel... |
| mc.pwbart | Predicting new observations based on a previously fitted BART... |
| mc.wbart | BART for continuous responses with parallel computation |
| medianInclusion.vs | Variable selection with DART |
| mixone | Generate data with independent and mixed-type predictors |
| mixtwo | Generate data with correlated and mixed-type predictors |
| pbart | Probit BART for binary responses with Normal latents |
| permute.vs | Permutation-based variable selection approach |
| predict.pbart | Predict new observations with a fitted BART model |
| predict.wbart | Predict new observations with a fitted BART model |
| pwbart | Predicting new observations with a previously fitted BART... |
| wbart | BART for continuous responses |
