R help - Nov 2005 - Poisson/negbin followed by jackknife

Folks,

Thanks for the help with the hier.part analysis.  All the problems
stemmed from an import problem which was solved with file.chose().

Now that I have the variables that I'd like to use I need to run some
GLM models.  I think I have that part under control but I'd like to use
a jackknife approach to model validation (I was using a hold out sample
but this seems to have fallen out of favor).  

I'd appreciate it if someone could just point me in the right direction
for the jackkife analysis given a particular distribution, coefficients,
etc.

Thanks,

Jeff

****************************************
Jeffrey A. Stratford, Ph.D.
Postdoctoral Associate
331 Funchess Hall
Department of Biological Sciences
Auburn University
Auburn, AL 36849
334-329-9198
FAX 334-844-9234
http://www.auburn.edu/~stratja

Do you really mean a jackknife or leave-one-out crossvalidation?  They are 
not the same, but the second is often incorrectly called the first.

In either case, I would point you at the book the 'boot' package
supports.
See for example its cv.glm function.

On Mon, 7 Nov 2005, Jeffrey Stratford wrote:
> Thanks for the help with the hier.part analysis.  All the problems
> stemmed from an import problem which was solved with file.chose().
>
> Now that I have the variables that I'd like to use I need to run some
> GLM models.  I think I have that part under control but I'd like to use
> a jackknife approach to model validation (I was using a hold out sample
> but this seems to have fallen out of favor).
>
> I'd appreciate it if someone could just point me in the right direction
> for the jackkife analysis given a particular distribution, coefficients,
> etc.
-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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