| ankara | benchmark_datasets | 
| automobile | Data concerning automobile prices. | 
| bartMachine | Build a BART Model | 
| bartMachineArr | Create an array of BART models for the same data. | 
| bartMachineCV | Build BART-CV | 
| bart_machine_get_posterior | Get Full Posterior Distribution | 
| bart_machine_num_cores | Get Number of Cores Used by BART | 
| bart_predict_for_test_data | Predict for Test Data with Known Outcomes | 
| baseball | benchmark_datasets | 
| boston | benchmark_datasets | 
| build_bart_machine | Build a BART Model | 
| build_bart_machine_cv | Build BART-CV | 
| calc_credible_intervals | Calculate Credible Intervals | 
| calc_prediction_intervals | Calculate Prediction Intervals | 
| check_bart_error_assumptions | Check BART Error Assumptions | 
| compactiv | benchmark_datasets | 
| cov_importance_test | Importance Test for Covariate(s) of Interest | 
| destroy_bart_machine | Destroy BART Model (deprecated - do not use!) | 
| dummify_data | Dummify Design Matrix | 
| extract_raw_node_data | Gets Raw Node data | 
| get_projection_weights | Gets Training Sample Projection / Weights | 
| get_sigsqs | Get Posterior Error Variance Estimates | 
| get_var_counts_over_chain | Get the Variable Inclusion Counts | 
| get_var_props_over_chain | Get the Variable Inclusion Proportions | 
| interaction_investigator | Explore Pairwise Interactions in BART Model | 
| investigate_var_importance | Explore Variable Inclusion Proportions in BART Model | 
| k_fold_cv | Estimate Out-of-sample Error with K-fold Cross validation | 
| linearity_test | Test of Linearity | 
| node_prediction_training_data_indices | Gets node predictions indices of the training data for new data. | 
| ozone | benchmark_datasets | 
| pd_plot | Partial Dependence Plot | 
| plot_convergence_diagnostics | Plot Convergence Diagnostics | 
| plot_y_vs_yhat | Plot the fitted Versus Actual Response | 
| pole | benchmark_datasets | 
| predict.bartMachine | Make a prediction on data using a BART object | 
| predict_bartMachineArr | Make a prediction on data using a BART array object | 
| print.bartMachine | Summarizes information about a 'bartMachine' object. | 
| rmse_by_num_trees | Assess the Out-of-sample RMSE by Number of Trees | 
| set_bart_machine_num_cores | Set the Number of Cores for BART | 
| summary.bartMachine | Summarizes information about a 'bartMachine' object. | 
| triazine | benchmark_datasets | 
| var_selection_by_permute | Perform Variable Selection using Three Threshold-based Procedures | 
| var_selection_by_permute_cv | Perform Variable Selection Using Cross-validation Procedure | 
| wine.red | benchmark_datasets | 
| wine.white | benchmark_datasets |