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mdgc
View on CRAN: Click
here
Download and install mdgc package within the R console
Install from CRAN:
install.packages("mdgc")
Install from Github:
library("remotes")
install_github("cran/mdgc") Install by package version:
library("remotes")
install_version("mdgc", "0.1.7") Attach the package and use:
library("mdgc")
Maintained by
Benjamin Christoffersen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-17
Latest Update: 2023-05-04
Description:
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.
How to cite:
Benjamin Christoffersen (2021). mdgc: Missing Data Imputation Using Gaussian Copulas. R package version 0.1.7, https://cran.r-project.org/web/packages/mdgc. Accessed 05 Jun. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for mdgc
Functions, R codes and Examples using
the mdgc R package
Some associated functions: get_mdgc . get_mdgc_log_ml . mdgc-package . mdgc . mdgc_fit . mdgc_impute . mdgc_log_ml . mdgc_start_value .
Some associated R codes: RcppExports.R . catch-routine-registration.R . mdgc-package.R . mdgc.R . Full mdgc package functions and examples
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