Package: heteromixgm
Type: Package
Title: Copula Graphical Models for Heterogeneous Mixed Data
Imports: Matrix, igraph, parallel, tmvtnorm, glasso, BDgraph, methods,
        stats, utils, MASS
Authors@R: c(person(given = "Sjoerd",
           family = "Hermes",
           role = c("aut", "cre"),
           email = "sjoerd.hermes@wur.nl"), 
           person(given = "Joost", family = "van Heerwaarden", role = "ctb"),
           person(given = "Pariya", family = "Behrouzi", role = "ctb"))
Version: 2.0.2
Maintainer: Sjoerd Hermes <sjoerd.hermes@wur.nl>
Description: 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>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.10)
NeedsCompilation: no
Packaged: 2024-08-18 11:16:32 UTC; sjoer
Author: Sjoerd Hermes [aut, cre],
  Joost van Heerwaarden [ctb],
  Pariya Behrouzi [ctb]
Repository: CRAN
Date/Publication: 2024-08-19 07:30:05 UTC
Built: R 4.6.0; ; 2026-04-28 04:49:34 UTC; unix
