MixedDataImpute: Missing Data Imputation for Continuous and Categorical Data using Nonparametric Bayesian Joint Models

Missing data imputation for continuous and categorical data, using nonparametric Bayesian joint models (specifically the hierarchically coupled mixture model with local dependence described in Murray and Reiter (2015); see 'citation("MixedDataImpute")' or http://arxiv.org/abs/1410.0438). See '?hcmm_impute' for example usage.

Install the latest version of this package by entering the following in R:
install.packages("MixedDataImpute")
AuthorJared S. Murray
Date of publication2016-02-07 09:20:13
MaintainerJared S. Murray <jsmurray@stat.cmu.edu>
LicenseGPL-3
Version0.1

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Files

inst
inst/CITATION
src
src/Makevars
src/common.h
src/StatlFunctions.cpp
src/stick.cpp
src/StatFunctions.h
src/hcmmld.cpp
src/clusters.cpp
src/clusters.h
src/hcmmld_pmn.h
src/Makevars.win
src/RcppExports.cpp
src/common.cpp
src/rng.h
src/rng.cpp
src/stick.h
src/hcmmld_mvreg.h
NAMESPACE
data
data/sipp08.rda
R
R/MixedDataImpute.R R/impute.R R/make_lookup.R R/sipp08.R R/prepare_data.R R/RcppExports.R R/hyperpars.R R/zzz.R
MD5
DESCRIPTION
man
man/prepare_data.Rd man/hcmm_impute.Rd man/MixedDataImpute.Rd man/hcmm_hyperpar.Rd man/remap_imputations.Rd man/sipp08.Rd

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