moewishart: Mixture-of-Experts Wishart Models for Covariance Data

Methods for maximum likelihood and Bayesian estimation for the Wishart mixture model and the mixture-of-experts Wishart (MoE-Wishart) model. The package provides four inference algorithms for these models, each implemented using the expectation–maximization (EM) algorithm for maximum likelihood estimation and a fully Bayesian approach via Gibbs-within-Metropolis–Hastings sampling.

Version: 1.0
Depends: R (≥ 4.1.0)
Imports: utils, stats, loo
Suggests: rmarkdown, knitr
Published: 2026-02-19
DOI: 10.32614/CRAN.package.moewishart (may not be active yet)
Author: The Tien Mai [aut], Zhi Zhao [aut, cre]
Maintainer: Zhi Zhao <zhi.zhao at medisin.uio.no>
BugReports: https://github.com/zhizuio/moewishart/issues
License: GPL-3
URL: https://github.com/zhizuio/moewishart
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: moewishart results

Documentation:

Reference manual: moewishart.html , moewishart.pdf
Vignettes: Introduction (source, R code)

Downloads:

Package source: moewishart_1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: moewishart_1.0.zip
macOS binaries: r-release (arm64): moewishart_1.0.tgz, r-oldrel (arm64): moewishart_1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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