Journal
COMPUTATIONAL STATISTICS & DATA ANALYSIS
Volume 53, Issue 11, Pages 3835-3841Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.csda.2009.04.001
Keywords
Intersection-union tests; Parametric bootstrap; Parameter estimation; Asymptotic maximum likelihood estimation; Ozone data
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This paper proposes a bootstrap goodness of fit test for the Generalized Pareto distribution (GPd) with shape parameter gamma. The proposed test is an intersection-union test which tests separately the cases of gamma >= 0 and gamma < 0 and rejects if both cases are rejected. If the test does not reject, then it is known whether the shape parameter gamma is either positive or negative. A Monte Carlo simulation experiment was conducted to assess the power of performance of the intersection-union test. The GPd hypothesis was tested on a data set containing Mexico City's ozone levels.(1) (C) 2009 Elsevier B.V. All rights reserved.
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