Estimating an endpoint with high-order moments

Stéphane Girard, Armelle Guillou () and Gilles Stupfler

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2012, vol. 21, issue 4, 697-729

Abstract: 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. Copyright Sociedad de Estadística e Investigación Operativa 2012

Keywords: Endpoint estimation; High-order moments; Consistency; Asymptotic normality; 62G32; 62G05 (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:testjl:v:21:y:2012:i:4:p:697-729

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DOI: 10.1007/s11749-011-0277-8

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