I am trying to fit a Gaussian Copula with t margins to my data (log returns of two stocks). It has already worked for a Gaussian Copula with normal margins with:
normcopula_dist = mvdc(copula=normalCopula(normrho,dim=2), margins=c("norm","norm"), paramMargins=list(list(mean=db_mu, sd=db_sd), list(mean=cb_mu, sd=cb_sd)))
My question is, how can I simulate my data with t margins? Here I can only set a parameter for df, but I need a t distribution also with mean and standard deviation matching my copula. Any help here? My idea was to create multivariate normal pseudo observations and then to transform them into t distribution and use their df for the estimation, but I am not quite sure, if it worksfine.