NPBayesImpute: Non-Parametric Bayesian Multiple Imputation for Categorical Data

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
MaintainerQuanli Wang <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the NPBayesImpute package in your browser

Any scripts or data that you put into this service are public.

NPBayesImpute documentation built on May 29, 2017, 11:12 p.m.