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) <doi:10.48550/arXiv.2102.02642>. The method is related to Hoff (2007) <doi:10.1214/07-AOAS107> and Zhao and Udell (2019) <doi:10.48550/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: 0.1.7
Depends: R (≥ 3.5.0)
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo, testthat, BH, psqn
Suggests: testthat, catdata
Published: 2023-05-04
DOI: 10.32614/CRAN.package.mdgc
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>
License: GPL-2
NeedsCompilation: yes
Materials: NEWS
In views: MissingData
CRAN checks: mdgc results


Reference manual: mdgc.pdf


Package source: mdgc_0.1.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mdgc_0.1.7.tgz, r-oldrel (arm64): mdgc_0.1.7.tgz, r-release (x86_64): mdgc_0.1.7.tgz, r-oldrel (x86_64): mdgc_0.1.7.tgz
Old sources: mdgc archive


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