Estimating an endpoint with high-order moments

• Stéphane Girard ^[2] ; Armelle Guillou ^[1] ; Gilles Stupfler ^[1]
  1. [1] University of Strasbourg

     University of Strasbourg

     Arrondissement de Strasbourg-Ville, Francia

     
  2. [2] INRIA Rhône-Alpes & LJK
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 21, Nº. 4, 2012, págs. 697-729
• Idioma: inglés
• DOI: 10.1007/s11749-011-0277-8
• Texto completo no disponible (Saber más ...)
• Resumen

  • We present a new method for estimating the endpoint of a unidimensional sample when the distribution function decreases at a polynomial rate to zero in the neighborhood of the endpoint. The estimator is based on the use of high-order moments of the variable of interest. It is assumed that the order of the moments goes to infinity, and we give conditions on its rate of divergence to get the asymptotic normality of the estimator. The good performance of the estimator is illustrated on some finite sample situations.