R help - Jul 2007 - cv.glm error function

I have a couple quick questions about the use of cv.glm for
cross-validation.

1. If we have a Poisson GLM with counts Y~Poisson(mu) and
ln(mu)=beta0+beta1*x1+..., is the prediction error (delta) that is output
from cv.glm provided in terms of the counts (y) or the (mu)?

2. Can cv.glm be used for negative binomial models fit using glm.nb? It
appears to work, but since NB models aren't strictly GLM's I wanted to
check.

Thanks!

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On Fri, 20 Jul 2007, Rachel Davidson wrote:
> I have a couple quick questions about the use of cv.glm for
> cross-validation.
>
> 1. If we have a Poisson GLM with counts Y~Poisson(mu) and
> ln(mu)=beta0+beta1*x1+..., is the prediction error (delta) that is output
> from cv.glm provided in terms of the counts (y) or the (mu)?
It is of prediction error as measured by the cost function.  Since y and 
mu are on the same scale I wonder if you meant was it on log scale?  If 
so, it is on the response scale.

The default cost function is probably not appropriate for a log-linear 
model.
> 2. Can cv.glm be used for negative binomial models fit using glm.nb? It
> appears to work, but since NB models aren't strictly GLM's I wanted
to
> check.
NB models are strictly glms, but glm.nb estimates parameters that glm does 
not, so no.
>
> Thanks!
>
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>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
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