# Bayesian Additive Regression Trees

## Documentation for package ‘bartMachine’ version 1.4.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

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
benchmark_datasets | 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
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