msgcop-package {msgcop} | R Documentation |
This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2006). It also provides a semiparametric imputation procedure for missing multivariate data.
Package: | msgcop |
Type: | Package |
Version: | 0.9 |
Date: | 2006-10-06 |
License: | GPL Version 2 or later |
This function produces MCMC samples from the posterior distribution of a correlation matrix, using a scaled inverse-Wishart prior distribution and a partial set likelihood. It also provides imputation for missing values in a multivariate dataset.
Peter Hoff <hoff@stat.washington.edu>
Hoff (2006) ``Marginal set likelihood for semiparametric copula estimation''
fit<-msgcop.mcmc(swiss) summary(fit) plot(fit)