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Threshold selection for extremes under a semiparametric model

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  • Juan Gonzalez
  • Daniela Rodriguez
  • Mariela Sued

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. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Juan Gonzalez & Daniela Rodriguez & Mariela Sued, 2013. "Threshold selection for extremes under a semiparametric model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(4), pages 481-500, November.
    • Handle: RePEc:spr:stmapp:v:22:y:2013:i:4:p:481-500
    DOI: 10.1007/s10260-013-0234-7
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    References listed on IDEAS

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    6. Hall, Peter, 1990. "Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 177-203, February.
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