heteromixgm
2.0.2Copula Graphical Models for Heterogeneous Mixed Data
Overview
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.
Install
Health
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- WARNING2026-06-0812 OK · 0 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 57%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 100%
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Package metadata
- First published
- 2023-02-27
- Total releases
- 5 / 3 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.10
- Bundled data
- 2.4 KB / 1 file
- Download size
- 19 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet