I need to be able to run a generalized linear model with a log() link
and a Weibull family, or something similar to deal with an extreme
value distribution.
I actually have a large dataset where this is apparently necessary.
It has to do with recovery of forensic samples from surfaces, where
as much powder as possible is collected. This apparently causes the
results to conform to some type of extreme value distribution, so
Weibull is a reasonable starting point for exploration.
I have tried ('surface' and 'team' are factors)
glm(surfcount ~ surface*team, data=powderd, family=Gamma(link='log'))
but this doesn't quite do the trick. The standardized deviance
residuals are still curved away from normal at the tails.
Thanks for any info you can give on this nonstandard model.
================================================================
Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: [EMAIL PROTECTED]
Least Cost Formulations, Ltd. URL: http://lcfltd.com/
824 Timberlake Drive Tel: 757-467-0954
Virginia Beach, VA 23464-3239 Fax: 757-467-2947
"Vere scire est per causas scire"
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