On Fri, 18 Apr 2008 13:30:10 -0700 (PDT), Luna Moon
<lunamoonmoon@[EMAIL PROTECTED]
> wrote:
> Hi all,
>
> In statistical modelling of an insurance problem, I wanted to model
> the relation between the some premium and the death incidents in a
> sample pool, consisting of say, 100, subjects.
>
> The model has a Poisson process as one of its component. Now we are
> looking at the problem of estimation the parameters of this model.
>
> The problem is that there is no death event in our data sample. Does
> that render the Poisson component of the model unidentifiable?
I suppose someone might apply the term "unidentifiable" but
that seems too weak.
When all the responses on a dichotomy are on one side,
you have "no information" for the purpose of most statistical
tests.
>
> I guess this is also a model-comparison problem -- with no event of
> death, can I distinguish between a model with the counting(Poisson)
> component vs. a model with no counting (Poisson) component? Does the
> information about "no death or no counts" is itself some information
> for identifying the counting model?
Statistically, you can model a rate as "low" and discard any
hypothesis that requires a higher rate. But this looks like an
experiment that failed to show anything, for lack of power.
--
Rich Ulrich
http://www.pitt.edu/~wpilib/index.html
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