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Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions

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  • Ahmad Aboubacrène Ag

    (Université Gaston Berger, LERSTAD, UFR SAT, BP 234, Saint-Louis, Sénégal)

  • Deme El Hadji

    (Université Gaston Berger, LERSTAD, UFR SAT, BP 234, Saint-Louis, Sénégal)

  • Diop Aliou

    (Université Gaston Berger, LERSTAD, UFR SAT, BP 234, Saint-Louis, Sénégal)

  • Girard Stéphane

    (Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, 38000Grenoble, France)

Abstract

We introduce a location-scale model for conditional heavy-tailed distributions when the covariate is deterministic. First, nonparametric estimators of the location and scale functions are introduced. Second, an estimator of the conditional extreme-value index is derived. The asymptotic properties of the estimators are established under mild assumptions and their finite sample properties are illustrated both on simulated and real data.

Suggested Citation

  • Ahmad Aboubacrène Ag & Deme El Hadji & Diop Aliou & Girard Stéphane, 2019. "Estimation of the tail-index in a conditional location-scale family of heavy-tailed distributions," Dependence Modeling, De Gruyter, vol. 7(1), pages 394-417, January.
    • Handle: RePEc:vrs:demode:v:7:y:2019:i:1:p:394-417:n:21
    DOI: 10.1515/demo-2019-0021
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    References listed on IDEAS

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