Package: NPBayesImputeCat
Type: Package
Title: Non-Parametric Bayesian Multiple Imputation for Categorical Data
Version: 0.5
Date: 2022-10-03
Author: Quanli Wang, Daniel Manrique-Vallier, Jerome P. Reiter and Jingchen Hu
Maintainer: Jingchen Hu <jingchen.monika.hu@gmail.com>
Description: These routines create multiple imputations of missing at random categorical data, and create multiply imputed synthesis of categorical data, with or without structural zeros. Imputations and syntheses are based on Dirichlet process mixtures of multinomial distributions, which is a non-parametric Bayesian modeling approach that allows for flexible joint modeling, described in Manrique-Vallier and Reiter (2014) <doi:10.1080/10618600.2013.844700>.
License: GPL (>= 3)
Depends: Rcpp (>= 0.10.2)
Imports: methods, rlang, reshape2, ggplot2, dplyr, bayesplot
LinkingTo: Rcpp
RcppModules: clcm
NeedsCompilation: yes
Repository: CRAN
Packaged: 2022-10-03 13:07:34 UTC; qw2192
Date/Publication: 2022-10-03 13:30:02 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 19:46:39 UTC; windows
Archs: i386, x64
