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.

Documentation

Manual: NPBayesImpute.pdf
Vignette: None available.

Maintainer: Quanli Wang <quanli at stat.duke.edu>

Author(s): Quanli Wang, Daniel Manrique-Vallier, Jerome P. Reiter and Jingchen Hu

Install package and any missing dependencies by running this line in your R console:

install.packages("NPBayesImpute")

Depends methods, Rcpp(>=0.10.2)
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Package NPBayesImpute
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Version 0.6
Published 2016-02-09
License GPL (>= 3)
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NeedsCompilation yes
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CRAN checks NPBayesImpute check results
Package source NPBayesImpute_0.6.tar.gz