bcf                     Fit Bayesian Causal Forests
predict.bcf             Takes a fitted bcf object produced by bcf()
                        along with serialized tree samples and produces
                        predictions for a new set of covariate values
summary.bcf             Takes a fitted bcf object produced by bcf() and
                        produces summary stats and MCMC diagnostics.
                        This function is built using the coda package
                        and meant to mimic output from
                        rstan::print.stanfit(). It includes, for key
                        parameters, posterior summary stats, effective
                        sample sizes, and Gelman and Rubin's
                        convergence diagnostics.  By default, those
                        parameters are: sigma (the error standard
                        deviation when the weights are all equal),
                        tau_bar (the estimated sample average treatment
                        effect), mu_bar (the average outcome under
                        control/z=0 across all observations in the
                        sample), and yhat_bat (the average outcome
                        under the realized treatment assignment across
                        all observations in the sample).
