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moewishart  

Mixture-of-Experts Wishart Models for Covariance Data
View on CRAN: Click here


Download and install moewishart package within the R console
Install from CRAN:
install.packages("moewishart")

Install from Github:
library("remotes")
install_github("cran/moewishart")

Install by package version:
library("remotes")
install_version("moewishart", "1.0")



Attach the package and use:
library("moewishart")
Maintained by
Zhi Zhao
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-19
Latest Update: 2026-02-19
Description:
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.
How to cite:
Zhi Zhao (2026). moewishart: Mixture-of-Experts Wishart Models for Covariance Data. R package version 1.0, https://cran.r-project.org/web/packages/moewishart. Accessed 21 Aug. 2026.
Previous versions and publish date:
(2026-07-09 06:32), 1.0 (2026-02-19 20:50), 1.1 (2026-04-21 18:42)
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Complete documentation for moewishart
Functions, R codes and Examples using the moewishart R package
Full moewishart package functions and examples
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