Karl Ove Hufthammer wrote:
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)?
Package sn has this facility I believe.
David Scott
--
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David Scott Department of Statistics
The University of Auckland, PB 92019
Auckland 1142, NEW ZEALAND
Phone: +64 9 923 5055, or +64 9 373 7599 ext 85055
Email: d.sc...@auckland.ac.nz, Fax: +64 9 373 7018
Director of Consulting, Department of Statistics
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