sbart: Sequential BART for Imputation of Missing Covariates

Implements the sequential BART (Bayesian Additive Regression Trees) approach to impute the missing covariates. The algorithm applies a Bayesian nonparametric approach on factored sets of sequential conditionals of the joint distribution of the covariates and the missingness and applying the Bayesian additive regression trees to model each of these univariate conditionals. Each conditional distribution is then sampled using MCMC algorithm. The published journal can be found at <> Package provides a function, seqBART(), which computes and returns the imputed values.

Getting started

Package details

AuthorMichael Daniels
MaintainerAarti Singh <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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sbart documentation built on May 1, 2019, 7:23 p.m.