If you mean using random effects which have a fat-tailed distribution this has been available in AD Model Builder's random effects package for some time now. The general idea is to start with a random effect assumed to be standard normal and then to transform it by the cumulative dist function for the normal and then by the inverse of the cumulative distribution function of the desired distribution function of the desired distribution. See http://admb-project.org There is a list there where you should be able to get advice.
-- David A. Fournier P.O. Box 2040, Sidney, B.C. V8l 3S3 Canada Phone/FAX 250-655-3364 http://otter-rsch.com ______________________________________________ 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.
