wishartinference: Bayesian Inference for the Wishart Distribution Parameters

Posterior inference for the shape parameter alpha and mean matrix mu in the model X_i ~ Wishart_p(2*alpha, Sigma), under both an improper prior and a proper Gamma/inverse-Wishart prior. The posterior mode is found via a Newton-within-EM algorithm and joint samples are drawn via rejection sampling.

Version: 0.1.0
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo, BH
Suggests: testthat (≥ 3.1.5)
Published: 2026-09-03
DOI: 10.32614/CRAN.package.wishartinference (may not be active yet)
Author: Philip Everson [aut], Hanqi Shi [aut, cre]
Maintainer: Hanqi Shi <hshi1 at swarthmore.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README
CRAN checks: wishartinference results

Documentation:

Reference manual: wishartinference.html , wishartinference.pdf

Downloads:

Package source: wishartinference_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): wishartinference_0.1.0.tgz, r-oldrel (arm64): wishartinference_0.1.0.tgz, r-release (x86_64): wishartinference_0.1.0.tgz, r-oldrel (x86_64): wishartinference_0.1.0.tgz

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