Bayesian inference for clustered extremes
type: Item
instance of: scholarly article
title: Bayesian inference for clustered extremes
zbMATH Open document ID: 1157.62028
author: Lee Fawcett
author: David Walshaw
published in: Extremes
publication date: 2009-02-28T00:00:00Z
review text: Bayesian inference for extremal index, mean cluster size and other cluster functionals of extremes in a dependent stationary sequence is considered. A Metropolis-Hastings sampler is described for sampling from the posterior distribution of parameters. Performance of the algorithm is investigated on simulated data. An application to a wind speed data is presented.
Mathematics Subject Classification ID: 62G32
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 65C60
zbMATH DE Number: 5520599
zbMATH Keywords: extremal index
zbMATH Keywords: mean cluster size
zbMATH Keywords: stationary time series
zbMATH Keywords: Metropolis-Hastings sampler
describes a project that uses: ismev
MaRDI profile type: Publication
full work available at URL: s10687-007-0054-y
OpenAlex ID: W2058028217
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DOI: 10.1007/S10687-007-0054-Y
description: scientific article; zbMATH DE number 5520599