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: | 1.1 |
| Depends: | R (≥ 4.1.0) |
| Imports: | loo, stats, utils, graphics |
| Suggests: | rmarkdown, knitr |
| Published: | 2026-04-21 |
| DOI: | 10.32614/CRAN.package.moewishart |
| 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 |
| Citation: | moewishart citation info |
| Materials: | README, NEWS |
| CRAN checks: | moewishart results |
| Reference manual: | moewishart.html , moewishart.pdf |
| Vignettes: |
Introduction (source, R code) |
| Package source: | moewishart_1.1.tar.gz |
| Windows binaries: | r-devel: moewishart_1.1.zip, r-release: moewishart_1.1.zip, r-oldrel: moewishart_1.1.zip |
| macOS binaries: | r-release (arm64): moewishart_1.1.tgz, r-oldrel (arm64): moewishart_1.0.tgz, r-release (x86_64): moewishart_1.1.tgz, r-oldrel (x86_64): moewishart_1.1.tgz |
| Old sources: | moewishart archive |
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