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Book Sections Year : 2007

A Goodness-of-fit Test for the Distribution Tail

Abstract

In order to check that a parametric model provides acceptable tail approximations, we present a test which compares the parametric estimate of an extreme upper quantile with its semiparametric estimate obtained by extreme value theory. To build this test, the sampling variations of these estimates are approximated through parametric bootstrap. Numerical Monte Carlo simulations explore the covering probability and power of the test. A real-data study illustrates these results.
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Dates and versions

hal-00814959 , version 1 (18-04-2013)

Identifiers

  • HAL Id : hal-00814959 , version 1
  • PRODINRA : 289937

Cite

Jean Diebolt, Myriam Garrido, Stéphane Girard. A Goodness-of-fit Test for the Distribution Tail. M. Ahsanullah and S.N.U.A. Kirmani. Topics in Extreme Values, Nova Science, New-York, pp.95-109, 2007, 978-1600217142. ⟨hal-00814959⟩
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