Bayesian Inference for the Wishart Distribution Parameters

---

Documentation for package ‘wishartinference’ version 0.1.0

• DESCRIPTION file
• Code demos. Use demo() to run them.
• Package README

Help Pages

gamma_inference	Bayesian inference for the Wishart shape parameter, gamma (p = 1) case
ldet	Log determinant of a positive definite matrix
lfafun_gamma	Log unnormalized posterior of alpha, gamma (p = 1) case
lfafun_improper	Log unnormalized marginal posterior of alpha under the improper prior
lfafun_proper	Log unnormalized marginal posterior of alpha under the proper prior
lgammap_export	Log of the multivariate Gamma function
mode_alphaEM	Find the posterior mode of alpha
mode_alphaEM_gamma	EM algorithm to find the posterior mode of alpha, gamma (p = 1) case
rejection_sampler	Rejection sampler for the joint posterior of (alpha, mu)
rejection_sampler_gamma	Rejection sampler for the joint posterior of (alpha, mu), gamma (p = 1) case
rwishart	Generate draws from a Wishart distribution
wishart_hello	Verify that the compiled library loaded correctly
wishart_inference	Bayesian inference for the Wishart shape parameter
wishart_stats	Compute sufficient statistics for Wishart observations