On Tue, 27 Oct 2009 18:06:02 -0400 Ben Bolker <bol...@ufl.edu> wrote: > If transforming your data brings you closer to satisfying > the assumptions of your analytic methods and having a sensible > analysis, then that's good. If it makes things worse, that's bad. > Other choices, depending on the situation, include robust methods > (for "outlier" problems); generalized linear models etc. (for > discrete data from standard distributions); models using t- instead > of normally distributed residuals;
I have sometimes wondered about this: Which functions/packages do you use to fit a (perhaps just a simple linear) model with t-distributed residuals (or residuals of a different distribution)? -- Karl Ove Hufthammer ______________________________________________ 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.
