Testing the tail-dependence based on the radial component
type: Item
instance of: scholarly article
title: Testing the tail-dependence based on the radial component
zbMATH Open document ID: 1157.62029
author: Melanie Frick
author: Edgar Kaufmann
author: Rolf-Dieter Reiss
published in: Extremes
publication date: 2009-02-28T00:00:00Z
review text: A test is proposed for testing the hypothesis \(H_0\) on the tail independence of bivariate random vector \((X,Y)\) components. \((X,Y)\) is assumed to belong to the domain of max-attraction of an extreme value distribution with reverse exponential margins. The test statistics is constructed by the application of the Neyman-Pearson approach to the limiting distribution \(F\) of \(X+Y\) conditioned on \(X+Y>C\) when \(C\to\infty\). (Note, that \(F(t)=t\) under \(H_0\) and \(F(t)=t^{1+\rho}\) under the alternative). Approximate maximum likelihood estimate for \(\rho\) is considered. The performance of the test is explored by simulations. An application to sea-waves data is presented.
Mathematics Subject Classification ID: 62G32
Mathematics Subject Classification ID: 62G10
Mathematics Subject Classification ID: 62E20
zbMATH DE Number: 5520586
zbMATH Keywords: bivariate generalized Pareto distribution
zbMATH Keywords: Pickands dependence function
zbMATH Keywords: uniformly most powerful Neyman-Pearson test
MaRDI profile type: Publication
full work available at URL: s10687-007-0037-z
OpenAlex ID: W1998419792
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DOI: 10.1007/S10687-007-0037-Z
description: scientific article; zbMATH DE number 5520586