Copyright: (C) 2012 Decision Analyst, Inc. (ChoiceModelR is a trademark

Author: Ryan Sermas, assisted by John V. Colias, Ph.D.
Authors@R: c(person("Ryan", "Sermas", role = "aut", email =
"Colias", role = c("ctb","cre"), email =
Maintainer: John V Colias <jcolias@decisionanalyst.com>

Authors@R: c(person("Ryan", "Sermas", role = "aut", email = "DecisionAnalystR@decisionanalyst.com"), person(c("John","V"), "Colias", role = c("ctb","cre"), email = "jcolias@decisionanalyst.com"), person("Decision Analyst, Inc.", role = "cph"))
Suggests: bayesm, MASS, lattice, Matrix, testthat (>= 3.0.0)
Description: Implements an MCMC algorithm to estimate a hierarchical multinomial logit model with a normal heterogeneity distribution. The algorithm uses a hybrid Gibbs Sampler with a random walk metropolis step for the MNL coefficients for each unit. Dependent variable may be discrete or continuous. Independent variables may be discrete or continuous with optional order constraints. Means of the distribution of heterogeneity can optionally be modeled as a linear function of unit characteristics variables.
Copyright: Copyright (C) 2012 Decision Analyst, Inc.; 604 Avenue H
East, Arlington, Texas 76011; www.decisionanalyst.com;
817-640-6166 (ChoiceModelR is a trademark of Decision Analyst,

Title: Cholesky Decomposition of the Wishart Distribution
Description: Sampling from the Cholesky factorization of a Wishart random
variable, sampling from the inverse Wishart distribution, sampling from
the Cholesky factorization of an inverse Wishart random variable,
computing densities for the Wishart and inverse Wishart distributions,
and computing the multivariate gamma and digamma functions.

the Cholesky factorization of an inverse Wishart random variable, sampling
from the pseudo Wishart distribution, sampling from the generalized
inverse Wishart distribution, computing densities for the Wishart
and inverse Wishart distributions, and computing the multivariate gamma

Author: Geoffrey Thompson [aut, cre] (<https://orcid.org/0000-0003-2436-8822>),