NPBayesImputeCat: Non-Parametric Bayesian Multiple Imputation for Categorical Data

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.

Getting started

Package details

AuthorQuanli Wang, Daniel Manrique-Vallier, Jerome P. Reiter and Jingchen Hu
MaintainerJingchen Hu <[email protected]>
LicenseGPL (>= 3)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the NPBayesImputeCat package in your browser

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

NPBayesImputeCat documentation built on May 2, 2019, 2:39 a.m.