Re: a simple(?) probability question...



On Jan 29, 6:54 pm, "Joe" <jconcor...@xxxxxxxxxxx> wrote:

[snip]

No, I am just saying that I expect the storm to occur once in 100
years,
that could be year #1 or year #99. My statement on this has always
been
that there is a 50:50 chance for the storm every year of the 100 year
term.

And this statement has always been completely wrong.


I think granularity of 1-year is appropriate since the underlying data
set is based
on annual data.

It is arguably not appropriate because, as has been stated before, the
storm *could* occur more than once in the same year. Admittedly the
probability of this happening is very small, and it makes little
difference to any calculated results, but the principle is there.

I think a time domain of 100 years is appropriate
since we are
concerned with a data value that is selected from a set that includes
the data for
a 100 year time frame.

Appropriate for what? The 100-year storm is *defined* such that it is
expected to occur once in 100 years. We can then, hopefully, use an
appropriate model to calculate (or, if you prefer, estimate) the
probability of its occurring some stated number of times in *any* time
interval.

While some analogies can be made to 10-year,
25-year, etc
storms, I think the storm cycles within these time periods are not
good representative
examples for the 100year storm. I believe it is not as simple at 100
year storm = 0.01 probability,
10-year storm = 0.10 probability. There is a unique character to the
100 year storm by
virtue of the long duration being considered, and the singularity of
the event within that
time frame.

I do not personally see why a 10-year storm model should not become a
100-year storm model simply by adjustment of parameters - as is the
case with a simple (or simplistic) binomial or Poisson model. However,
I don't know enough about weather modelling to say anything definite
about other models. Certainly you would need a better explanation than
this to convince that there is a qualitative difference.

.

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