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Activity Number:
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72
- Methods for Extreme Values in Environmental Data
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Section on Statistics and the Environment
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Abstract #312960
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Title:
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Reference Priors for the Generalized Extreme Value Distribution
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Author(s):
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Likun Zhang* and Benjamin A Shaby
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Companies:
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Penn State University and Colorado State University
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Keywords:
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Noninformative;
Objective Bayes
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Abstract:
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We derive a collection of reference prior distributions for Bayesian analysis under the three-parameter generalized extreme value (GEV) distribution. These priors are based on an established formal definition of noninformativeness. They depend on the ordering of the three parameters, and we show that the GEV is unusual in that some orderings fail to yield proper posteriors for any sample size. We also consider a reparametrization that explicitly regards return level estimation, which is the most common goal of GEV analysis, to be the most important inferential task. We investigate the properties of the derived priors using simulation and apply them to an analysis of a fire threat index in California.
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Authors who are presenting talks have a * after their name.
