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heteromixgm

Copula Graphical Models for Heterogeneous Mixed Data

A multi-core R package that allows for the statistical modeling of multi-group multivariate mixed data using Gaussian graphical models. Combining the Gaussian copula framework with the fused graphical lasso penalty, the 'heteromixgm' package can handle a wide variety of datasets found in various sciences. The package also includes an option to perform model selection using the AIC, BIC and EBIC information criteria, a function that plots partial correlation graphs based on the selected precision matrices, as well as simulate mixed heterogeneous data for exploratory or simulation purposes and one multi-group multivariate mixed agricultural dataset pertaining to maize yields. The package implements the methodological developments found in Hermes et al. (2024) <doi:10.1080/10618600.2023.2289545>.

Versions across snapshots

VersionRepositoryFileSize
2.0.2 rolling source/ R- heteromixgm_2.0.2.tar.gz 18.7 KiB
2.0.2 rolling linux/jammy R-4.5 heteromixgm_2.0.2.tar.gz 106.5 KiB
2.0.2 rolling linux/noble R-4.5 heteromixgm_2.0.2.tar.gz 106.5 KiB
2.0.2 latest source/ R- heteromixgm_2.0.2.tar.gz 18.7 KiB
2.0.2 latest linux/jammy R-4.5 heteromixgm_2.0.2.tar.gz 106.5 KiB
2.0.2 latest linux/noble R-4.5 heteromixgm_2.0.2.tar.gz 106.5 KiB
2.0.2 2026-04-23 source/ R- heteromixgm_2.0.2.tar.gz 18.7 KiB
2.0.2 2026-04-09 windows/windows R-4.5 heteromixgm_2.0.2.zip 109.8 KiB
2.0.2 2025-04-20 source/ R- heteromixgm_2.0.2.tar.gz 18.7 KiB

Dependencies (latest)

Imports