Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches

We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.

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Year of publication:	2015-01
Authors:	Bolancé, Catalina ; Bahraoui, Zuhair ; Alemany, Ramon
Institutions:	Xarxa de Referència en Economia Aplicada (XREAP)
Subject:	Transformed kernel estimation \| cumulative distribution function \| extreme value distribution

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Extent:	application/pdf
Series:	Working Papers.
Type of publication:	Book / Working Paper
Notes:	Number XREAP2015-01 36 pages
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011124481