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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.

Versions across snapshots

VersionRepositoryFileSize
0.1.7 rolling linux/jammy R-4.5 mdgc_0.1.7.tar.gz 670.6 KiB
0.1.7 rolling linux/noble R-4.5 mdgc_0.1.7.tar.gz 680.9 KiB
0.1.7 rolling source/ R- mdgc_0.1.7.tar.gz 357.2 KiB
0.1.7 latest linux/jammy R-4.5 mdgc_0.1.7.tar.gz 670.6 KiB
0.1.7 latest linux/noble R-4.5 mdgc_0.1.7.tar.gz 680.9 KiB
0.1.7 latest source/ R- mdgc_0.1.7.tar.gz 357.2 KiB
0.1.7 2026-04-26 source/ R- mdgc_0.1.7.tar.gz 357.2 KiB
0.1.7 2026-04-23 source/ R- mdgc_0.1.7.tar.gz 357.2 KiB
0.1.7 2026-04-09 windows/windows R-4.5 mdgc_0.1.7.zip 1.0 MiB
0.1.7 2025-04-20 source/ R- mdgc_0.1.7.tar.gz 357.2 KiB

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