Hi, Forgive me if I seem naive, I'm tackling multivariate stats for the first time!
Q. I'd like to know if there are packages that can be used to simulate random draws from general multivariate (joint) PDF functions when ONLY the independent marginal PDFs are known (RV means and covariance or correlation matrix)? Q. I see there is a Markov Chain Monte Carlo package, but the mcmc documentation is not clear enough for me to be able to use it to simulate draws from joint PDFs. I'd like to automate this type of task. Is there aother Monte Carlo strategy that has an R interface? Can anyone help? Other Stats Questions/comments: * I'm aware the underlying joint PDF cannot be uniquely determined, but I assume for certain simulation purposes sampling correlated RV's from the marginal PDFs is sufficient (eg., my purpose is uncertainty or error propagation, using say the ISO GUM Supplement 1 Monte Carlo approach). Is this assumption correct, or for error propagation are there strong caveats to observe. (ASIDE: The ISO GUM Supp.-1 does not provide advice on how to simulate RV's drawn from multivariate PDFS for other than the multivariate normal dist. for which I can easily use the mvtnorm or mnormt packages.) Thanks in advance. bms. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
