Local robust and asymptotically unbiased estimation of conditional Pareto-type tails

• Goedele Dierckx ^[2] ; Yuri Goegebeur ^[1] ; Armelle Guillou ^[3]
  1. [1] University of Southern Denmark

     University of Southern Denmark

     Dinamarca

     
  2. [2] Research Centre for Mathematical Economics, Econometrics and Statistics
  3. [3] Université de Strasbourg et CNRS

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• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 23, Nº. 2, 2014, págs. 330-355
• Idioma: inglés
• DOI: 10.1007/s11749-013-0350-6
• Texto completo no disponible (Saber más ...)
• Resumen

  • We introduce a non-parametric robust and asymptotically unbiased estimator for the tail index of a conditional Pareto-type response distribution in presence of random covariates. The estimator is obtained from local fits of the extended Pareto distribution to the relative excesses over a high threshold using an adjusted minimum density power divergence estimation technique. We derive the asymptotic properties of the proposed estimator under some mild regularity conditions, and also investigate its finite sample performance with a small simulation experiment. The practical applicability of the methodology is illustrated on a dataset of calcium content measurements of soil samples.