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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>.
| Version: | 2.0.2 |
| Depends: | R (≥ 3.10) |
| Imports: | Matrix, igraph, parallel, tmvtnorm, glasso, BDgraph, methods, stats, utils, MASS |
| Published: | 2024-08-19 |
| DOI: | 10.32614/CRAN.package.heteromixgm |
| Author: | Sjoerd Hermes [aut, cre], Joost van Heerwaarden [ctb], Pariya Behrouzi [ctb] |
| Maintainer: | Sjoerd Hermes <sjoerd.hermes at wur.nl> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | heteromixgm results |
| Reference manual: | heteromixgm.pdf |
| Package source: | heteromixgm_2.0.2.tar.gz |
| Windows binaries: | r-devel: heteromixgm_2.0.2.zip, r-release: heteromixgm_2.0.2.zip, r-oldrel: heteromixgm_2.0.2.zip |
| macOS binaries: | r-release (arm64): heteromixgm_2.0.2.tgz, r-oldrel (arm64): heteromixgm_2.0.2.tgz, r-release (x86_64): heteromixgm_2.0.2.tgz, r-oldrel (x86_64): heteromixgm_2.0.2.tgz |
| Old sources: | heteromixgm archive |
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