Bayesian Additive Regression Trees using Bayesian Model Averaging


[Up] [Top]

Documentation for package ‘bartBMA’ version 1.0

Help Pages

bartBMA Bayesian Additive Regression Trees Using Bayesian Model Averaging (BART-BMA)
bartBMA.default Bayesian Additive Regression Trees Using Bayesian Model Averaging (BART-BMA)
bartBMA_with_ITEs_exact_par Prediction intervals for bart-bma output obtained using linear algebra to obtain means and variances, and using bisection to find the quantiles of the mixture of t distributions.
ITEs_bartBMA ITE Predictions (in-sample) using bartBMA and the method described by Hill (2011)
ITEs_bartBMA_exact_par Estimate ITEs and obtain credible intervals (in-sample or out-of-sample).
ITEs_CATT_bartBMA_exact_par Estimate ITEs, CATE, CATT, CATNT and obtain credible intervals (in-sample or out-of-sample).
predict_bartBMA Predictions for a new dataset using an existing bartbma object
predict_probit_bartBMA Predictions for a new dataset using an existing probit_bartBMA object
preds_bbma_lin_alg Predictions for bart-bma output obtained from the posterior probability weighted averaged of the posterior means for each model
pred_expectation_intervals_bbma_GS Prediction intervals for bart-bma output
pred_intervals_bbma_GS Prediction intervals for bart-bma output
pred_intervals_new_initials_GS Prediction intervals for bart-bma output
pred_ints_exact Prediction intervals for bart-bma output obtained using linear algebra to obtain means and variances, and using bisection to find the quantiles of the mixture of t distributions.
pred_ints_exact_par Prediction intervals for bart-bma output obtained using linear algebra to obtain means and variances, and using bisection to find the quantiles of the mixture of t distributions.
pred_means_bbma_GS Predictions for bart-bma output obtained from a Gibbs sampler
pred_means_bbma_new_initials_GS Predictions for bart-bma output obtained from a Gibbs sampler
probit_bartBMA Probit BART_BMA for classification of a binary variable
probit_bartBMA.default Probit BART_BMA for classification of a binary variable
varImpScores Variable importances as defined by Hernandez et al. (2018)
varIncProb Variable inclusion probabilities as defined by Linero (2018)