[Statistics & Probability Seminar]
Generalized Pareto copulas: a key to multivariate extremes
This talk reviews generalized Pareto copulas (GPC), which turn out to be a key to multivariate extreme value theory. Any GPC can be represented in an easy analytic way using a particular type of norm on Rd, called D-norm. The characteristic property of a GPC is its exceedance stability. GPC might help to end the debate: What is a multivariate generalized Pareto distribution? We present an easy way how to simulate data from an arbitrary GPC and, thus, from an arbitrary generalized Pareto distribution.
[Support from the LMS Research in Pairs Scheme (Scheme 4) is gratefully acknowledged.]
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