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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) <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
 [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 |
| Materials: |
NEWS |
| In views: |
MissingData |
| CRAN checks: |
mdgc results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=mdgc
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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