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Michael Stein, University of Chicago

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Some thoughts on the use of extreme value theory for temperature extremes
02 March 2017 from 4:00 PM to 5:00 PM
201 Thomas Building
Contact Name
Lorey Burghard
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Most studies of extremes focus on fat-tailed distributions. However,
temperature distributions tend to be thin-tailed. Indeed, when one fits
extreme value distributions to temperature data, one generally obtains
negative estimates of the shape parameter, which implies that
temperature distributions are bounded.  This talk will explore a number
of issues that arise when applying extreme value methods to daily
temperature data, including the use of long climate model runs to
estimate properties of extremes, taking account of seasonality and
models for dependence.  I will also describe a weighted composite
likelihood approach to estimating the upper tail of a distribution that
avoids having to pick a sharp cutoff for which observations are excluded
from the estimation.


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