CRAN/E | heteromixgm

heteromixgm

Copula Graphical Models for Heterogeneous Mixed Data

Installation

About

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, 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. (2022) doi:10.48550/arXiv.2210.13140.

Key Metrics

Version 1.0.0
R ≥ 3.10
Published 2023-06-29 311 days ago
Needs compilation? no
License GPL-3
CRAN checks heteromixgm results

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Maintainer

Maintainer

Sjoerd Hermes

sjoerd.hermes@wur.nl

Authors

Sjoerd Hermes

aut / cre

Joost van Heerwaarden

ctb

Pariya Behrouzi

ctb

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

heteromixgm archive

Depends

R ≥ 3.10

Imports

Matrix
igraph
parallel
tmvtnorm
glasso
BDgraph
methods
stats
utils
MASS