Description
Bayesian Copula Regression.
Description
Tools for Bayesian copula generalized linear models (GLMs). The sampling scheme is based on Pitt, Chan, and Kohn (2006) <doi:10.1093/biomet/93.3.537>. Regression parameters (including coefficients and dispersion parameters) are estimated via the adaptive random walk Metropolis approach developed by Haario, Saksman, and Tamminen (1999) <doi:10.1007/s001800050022>. The prior for the correlation matrix is based on Hoff (2007) <doi:10.1214/07-AOAS107>.
README.md
bayescopulareg
Bayesian analysis of multivariate generalized linear models via copulas
This package contains two main functions.
bayescopulaglmsamples from the posterior of a multivariate generalized linear model (currently supported families arepoisson,gaussian,binomial, andgamma.predict.bayescopulaglmwhich samples from the predictive posterior density of abayescopulaglmobject.