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.

AuthorQuanli Wang, Daniel Manrique-Vallier, Jerome P. Reiter and Jingchen Hu
Date of publication2016-02-09 20:53:48
MaintainerQuanli Wang <quanli@stat.duke.edu>
LicenseGPL (>= 3)
Version0.6

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Files in this package

NPBayesImpute
NPBayesImpute/inst
NPBayesImpute/inst/doc
NPBayesImpute/inst/doc/LCM_Zeros_Imputation_RMaterial.pdf
NPBayesImpute/src
NPBayesImpute/src/CLcm.cpp
NPBayesImpute/src/Makevars
NPBayesImpute/src/CData.h
NPBayesImpute/src/CParam.cpp
NPBayesImpute/src/CParam.h
NPBayesImpute/src/SpecialFunctions.cpp
NPBayesImpute/src/MersenneTwister.h
NPBayesImpute/src/CEnv.cpp
NPBayesImpute/src/CLcm.h
NPBayesImpute/src/lczmain.cpp
NPBayesImpute/src/CTrace.cpp
NPBayesImpute/src/CArrayND.h
NPBayesImpute/src/CEnv.h
NPBayesImpute/src/CData.cpp
NPBayesImpute/src/CTrace.h
NPBayesImpute/src/margin_conditions.h
NPBayesImpute/src/Makevars.win
NPBayesImpute/src/SpecialFunctions.h
NPBayesImpute/src/margin_conditions.cpp
NPBayesImpute/NAMESPACE
NPBayesImpute/demo
NPBayesImpute/demo/example.R
NPBayesImpute/demo/00Index
NPBayesImpute/demo/example_short.R
NPBayesImpute/data
NPBayesImpute/data/NYMockexample.RData
NPBayesImpute/data/NYexample.RData
NPBayesImpute/R
NPBayesImpute/R/ArrayUtils.R NPBayesImpute/R/zzz.R
NPBayesImpute/MD5
NPBayesImpute/DESCRIPTION
NPBayesImpute/man
NPBayesImpute/man/CreateModel.Rd NPBayesImpute/man/GetMCZ.Rd NPBayesImpute/man/MCZ.Rd NPBayesImpute/man/Rcpp_Lcm.Rd NPBayesImpute/man/GetDataFrame.Rd NPBayesImpute/man/Rcpp_Lcm-class.Rd NPBayesImpute/man/Lcm.Rd NPBayesImpute/man/UpdateX.Rd NPBayesImpute/man/X.Rd NPBayesImpute/man/NPBayesImput-package.Rd

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