Package: mdgc 0.1.7
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.
Authors:
mdgc_0.1.7.tar.gz
mdgc_0.1.7.tar.gz(r-4.5-noble)mdgc_0.1.7.tar.gz(r-4.4-noble)
mdgc.pdf |mdgc.html✨
mdgc/json (API)
NEWS
# Install 'mdgc' in R: |
install.packages('mdgc', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/boennecd/mdgc/issues
Last updated 2 years agofrom:187b9760d7. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 10 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 10 2024 |
Exports:get_mdgcget_mdgc_log_mlmdgcmdgc_fitmdgc_imputemdgc_log_mlmdgc_start_value
Dependencies:BHbriocallrclicrayondescdiffobjdigestevaluatefsgluejsonlitelatticelifecyclemagrittrMatrixpkgbuildpkgloadpraiseprocessxpspsqnR6RcppRcppArmadilloRcppEigenrlangrprojroottestthatwaldowithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
mdgc: Missing Data imputation using Gaussian Copulas | mdgc-package _PACKAGE |
Get mdgc Object | get_mdgc |
Get Pointer to C++ Object to Approximate the Log Marginal Likelihood | get_mdgc_log_ml get_mdgc_log_ml.data.frame get_mdgc_log_ml.default get_mdgc_log_ml.mdgc |
Perform Model Estimation and Imputation | mdgc |
Estimate the Model Parameters | mdgc_fit |
Impute Missing Values | mdgc_impute |
Evaluate the Log Marginal Likelihood and Its Derivatives | mdgc_log_ml |
Get Starting Value for the Covariance Matrix Using a Heuristic | mdgc_start_value mdgc_start_value.default mdgc_start_value.mdgc |