Package: sbart
Type: Package
Title: Sequential BART for Imputation of Missing Covariates
Version: 0.1.0
Author: Michael Daniels
Maintainer: Aarti Singh <mdstat2016@gmail.com>
Description: 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 <https://doi.org/10.1093/biostatistics/kxw009>
     Package provides a function, seqBART(), which computes and returns the imputed values.
License: MIT + file LICENSE
LazyData: TRUE
RoxygenNote: 6.0.1
Depends: R (>= 2.10)
Imports: LaplacesDemon, msm, Rcpp
LinkingTo: Rcpp
Suggests: testthat
NeedsCompilation: yes
Packaged: 2017-03-22 19:38:15 UTC; as82986
Repository: CRAN
Date/Publication: 2017-03-23 06:18:20 UTC
