Try maximizing the log-likelihood and using the log=TRUE argument to dmst. (You have told us so little about what you are doing that we can but guess at what you mean by `write an mle procedure': what is wrong with st.mle, for example?)
On Tue, 28 Mar 2006, Konrad Banachewicz wrote: > Dear All, > I am working with skewed-t copula in my research recently, so I needed to > write an mle > procedure instead of using a standard fit one; I stick to the sn package. On > subsamples of the entire population that I deal with, everything is fine. > However, on the total sample (difference in cross-sectional > dimension: 30 vs 240) things go wrong - the objective function diverges to > infinity. I located the "rotten" line > to be > > t1 <- dmst(vector, mu, P, alpha, nu) > > where "vector" is the matrix row, on which I evaluate my likelihood and the > rest in parametrized in a standard > way, just as the help pages give it. In large dimensions, I get a zero value > of the density (which is probably due to numerical issues). I tried the > following dummy example > > t1 <- rmst(1,mu,P,alpha, nu) > t2 <- dmst(t1, mu, alpha,nu) > > and t2 remains to be zero. Can anyone help me on this one? > > thanks in advance, > Konrad > > -- > "We are what we pretend to be, so we must be careful about what we pretend > to be" > > Kurt Vonnegut Jr. "Mother Night" > > [[alternative HTML version deleted]] > > ______________________________________________ > [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 > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [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
