Package: NPBayesImpute
Type: Package
Title: Non-parametric Bayesian Multiple Imputation for Categorical Data
Version: 0.4
Date: 2014-04-05
Author: Quanli Wang, Daniel Manrique-Vallier, Jerome P. Reiter and Jingchen Hu
Maintainer: Quanli Wang <quanli@stat.duke.edu>
Description: These routines create multiple imputations of missing at random categorical data, with or without structural zeros. Imputations are based on Dirichlet process mixtures of multinomial distributions, which is a non-parametric Bayesian modeling approach that allows for flexible joint modeling.
License: GPL (>= 3)
Depends: methods, Rcpp (>= 0.10.2)
LinkingTo: Rcpp
RcppModules: clcm
Packaged: 2014-11-13 16:27:47 UTC; quanli
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-11-13 18:25:43
