NPBayesImpute: Non-Parametric Bayesian Multiple Imputation for Categorical Data
Version 0.6

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.

Getting started

Package details

AuthorQuanli Wang, Daniel Manrique-Vallier, Jerome P. Reiter and Jingchen Hu
Date of publication2016-02-09 20:53:48
MaintainerQuanli Wang <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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NPBayesImpute documentation built on May 29, 2017, 11:12 p.m.