Hi all

I am searching for a tool that would help me to identify weather patterns
that influence the prevalence of a pathogen, 'Pn'.

Say, I have annual prevalence data (collected in April) and I know that the
prevalence of 'Pn' is affected by the weather conditions since November. I
also have daily data for different weeather variables.

The objective is to identify the relationship between the weather from
Nov-Mar and the prevalence of Pn. We know that weather has an influence on
Pn. The question is to find out weather from which period is relevant or
what kind of weather is relevant. It could be that the first two winter
months (Nov-Dec) is the decisive factor or that a certain weather situation
(like 20 consecutive days of below zero conditions) occuring at any time is
important or a combination of both.

I have tried correlations between prevalence and monthly means for Mar,
Feb-Mar, Jan-Mar and so on and nothing definite turned up. I could also do
it on a weekly basis manually. But I wonder if there is a tool that uses a
moving window of different sizes (say, from a min size of 1 week to a max
of 4 months) and checks correlations for each of these periods.

I am thinking of ARMA, but my present intention is not to forecast but only
to study. Can it still be used? Or ARMA in combination with multivariate
analysis to study the relative importance of each weather variable.

Any suugestions are welcome. I have used R for basic stats analysis but
never worked with time-series data or the advanced tools of data mining.
So, it could also be possible I am not thinking along the right lines. Feel
free to correct if I am looking in the wrong place.

Thank you
Anto

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