I think you are off-track because max.loss does not sound like a
proper Y variable. Because max.loss is an amount that is known, in the
insurance applications I have seen it would have been modeled within
an offset term. Many of the examples have used number of ships or
buildings or the person years of exposure but I do not see that the
general strategy is limited to only such considerations.
I would also suggest that you consider links other than Gaussian,
perhaps negative binomial.
The task for the analyst is then to translate output from the chosen
model into interpretable meaning on the scale of interest, but I
assume your course instructor will help with that.
--
David Winsemius
On Apr 28, 2009, at 11:34 AM, mathallan wrote:
Hi
I got a dataset
loss max.loss grp
1 10 50 2
2 15 33 1
3 18 49 2
4 33 38 1
5 8 50 3
6 19 29 1
7 22 51 4
8 50 50 2
9 16 38 1
10 24 30 3
were loss and max.loss are monetary values (in dollar). Grp is group
number.
By use of GLM, I have to determine the effect of max.loss and grp (and
interactions between them) on loss. My question is how to do this.
Is it something like
glm(max.loss~loss,family=gaussian(link="identity")
were ofcourse I can change gaussian with Gamma,... and link with
log,...
But am I on right track, or what should I change?
Thanks
--
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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