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Threshold selection for extremes under a semiparametric model

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Abstract

In this work we propose a semiparametric likelihood procedure for the threshold selection for extreme values. This is achieved under a semiparametric model, which assumes there is a threshold above which the excess distribution belongs to the generalized Pareto family. The motivation of our proposal lays on a particular characterization of the threshold under the aforementioned model. A simulation study is performed to show empirically the properties of the proposal and we also compare it with other estimators.

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Acknowledgments

We are grateful to the anonymous referees and the editor for their comments that have largely contributed to improve the original manuscript, shedding light on several issues. We also thank Damian and Lucio for their careful reading of this manuscript. This research was partially supported by Grants pip 112-200801-00216 and 0592 from conicet, pict 0821 and 0883 from anpcyt and 20020090100208 and 20020100300057 from the Universidad de Buenos Aires at Buenos Aires, Argentina.

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Authors and Affiliations

  1. Universidad de Buenos Aires, Ciudad Universitaria, Intendente Giraldes 2160, C1428EGA , Buenos Aires, Argentina

    Juan Gonzalez, Daniela Rodriguez & Mariela Sued

  2. CONICET, Buenos Aires, Argentina

    Daniela Rodriguez & Mariela Sued

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  1. Juan Gonzalez
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  2. Daniela Rodriguez
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  3. Mariela Sued
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Correspondence to Mariela Sued.

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Gonzalez, J., Rodriguez, D. & Sued, M. Threshold selection for extremes under a semiparametric model. Stat Methods Appl 22, 481–500 (2013). https://doi.org/10.1007/s10260-013-0234-7

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