On Tue, 28 Mar 2006 13:11:02 +0200, Konrad Banachewicz wrote: KB> P is an identity matrix 240X240, mu and alpha are vectors of zeros KB> 240X1, nu equals 10, so alltogether You need: KB> P <- matrix(0,244,244) KB> diag(P) <- 1 KB> nu <- 10 KB> alpha <- rep(0,244) KB> mu <- rep(0,244) KB> require(sn) KB> t1 <- rmst(1,mu,P, alpha, nu) KB> t2 <- dmst(t1,mu,P,alpha,nu) KB> KB>
With such a large dimension, numerical problems are obiquitous. At the very least, I suggest that you work on the log scale: R> t2 <- dmst(t1,mu,P,alpha,nu, log=TRUE) R> t2 [1] -250.3 R> exp(t2) [1] 2.002e-109 The next release of the 'sn' package will handle this sort of things in a more consisent way (the R code is largely updated, but the documentation is far behind..) -- Adelchi Azzalini <[EMAIL PROTECTED]> Dipart.Scienze Statistiche, Università di Padova, Italia tel. +39 049 8274147, http://azzalini.stat.unipd.it/ KB> KB> > KB> > please supply the ingredients needed to reproduce the problem KB> > that you have faced (including the values of the parameters KB> > mu,P,alpha,nu, among the rest) KB> > KB> > best wishes, KB> > KB> > Adelchi Azzalini KB> > KB> > KB> ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
