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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1 |
rolling linux/jammy R-4.5 | moewishart_1.1.tar.gz |
177.7 KiB |
1.1 |
rolling linux/noble R-4.5 | moewishart_1.1.tar.gz |
177.8 KiB |
1.1 |
rolling source/ R- | moewishart_1.1.tar.gz |
96.8 KiB |
1.1 |
latest linux/jammy R-4.5 | moewishart_1.1.tar.gz |
177.7 KiB |
1.1 |
latest linux/noble R-4.5 | moewishart_1.1.tar.gz |
177.8 KiB |
1.1 |
latest source/ R- | moewishart_1.1.tar.gz |
96.8 KiB |
1.1 |
2026-04-26 source/ R- | moewishart_1.1.tar.gz |
96.8 KiB |
1.1 |
2026-04-23 source/ R- | moewishart_1.1.tar.gz |
96.8 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | moewishart_1.0.zip |
122.7 KiB |