sbart (0.1.1)

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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.

Maintainer: Aarti Singh
Author(s): Michael Daniels

License: MIT + file LICENSE

Uses: LaplacesDemon, msm, Rcpp, testthat
Reverse suggests: BART

Released over 1 year ago.

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