NPBayesImpute (0.6)

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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.

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

License: GPL (>= 3)

Uses: Rcpp

Released almost 4 years ago.

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