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) . The method is related to Hoff (2007) and Zhao and Udell (2019) 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) in addition to also support multinomial variables.


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install.packages("mdgc")

0.1.5 by Benjamin Christoffersen, 10 days ago


https://github.com/boennecd/mdgc


Report a bug at https://github.com/boennecd/mdgc/issues


Browse source code at https://github.com/cran/mdgc


Authors: Benjamin Christoffersen [cre, aut] , Alan Genz [cph] , Frank Bretz [cph] , Torsten Hothorn [cph] , R-core [cph] , Ross Ihaka [cph]


Documentation:   PDF Manual  


GPL-2 license


Imports Rcpp

Suggests testthat, catdata

Linking to Rcpp, RcppArmadillo, testthat, BH, psqn

System requirements: C++14


See at CRAN