mdgc: Missing Data Imputation Using Gaussian Copulas

Provides functions to impute missing values using Gaussian copulas for mixed data types as described by Christoffersen et al. (2021) <arXiv:2102.02642>. The method is related to Hoff (2007) <doi:10.1214/07-AOAS107> and Zhao and Udell (2019) <arXiv:1910.12845> but differs by making a direct approximation of the log marginal likelihood using an extended version of the Fortran code created by Genz and Bretz (2002) <doi:10.1198/106186002394> in addition to also support multinomial variables.

Version: 0.1.5
Depends: R (≥ 3.5.0)
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo, testthat, BH, psqn
Suggests: testthat, catdata
Published: 2021-06-14
Author: Benjamin Christoffersen ORCID iD [cre, aut], Alan Genz [cph], Frank Bretz [cph], Torsten Hothorn [cph], R-core [cph], Ross Ihaka [cph]
Maintainer: Benjamin Christoffersen <boennecd at gmail.com>
BugReports: https://github.com/boennecd/mdgc/issues
License: GPL-2
URL: https://github.com/boennecd/mdgc
NeedsCompilation: yes
SystemRequirements: C++14
Materials: NEWS
In views: MissingData
CRAN checks: mdgc results

Documentation:

Reference manual: mdgc.pdf

Downloads:

Package source: mdgc_0.1.5.tar.gz
Windows binaries: r-devel: mdgc_0.1.5.zip, r-release: mdgc_0.1.5.zip, r-oldrel: mdgc_0.1.5.zip
macOS binaries: r-release (arm64): mdgc_0.1.5.tgz, r-oldrel (arm64): mdgc_0.1.5.tgz, r-release (x86_64): mdgc_0.1.5.tgz, r-oldrel (x86_64): mdgc_0.1.5.tgz
Old sources: mdgc archive

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