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Title: Nonparametric estimation of extreme conditional quantiles
Authors: Beirlant, Jan ×
De Wet, T
Goegebeur, Yuri #
Issue Date: 2004
Publisher: Taylor & francis ltd
Series Title: Journal of statistical computation and simulation vol:74 issue:8 pages:567-580
Abstract: The estimation of extreme conditional quantiles is an important issue in different scientific disciplines. Up to now, the extreme value literature focused mainly on estimation procedures based on independent and identically distributed samples. Our contribution is a two-step procedure for estimating extreme conditional quantiles. In a first step nonextreme conditional quantiles are estimated nonparametrically using a local version of [Koenker, R. and Bassett, G. (1978). Regression quantiles. Econometrica , 46 , 33-50.] regression quantile methodology. Next, these nonparametric quantile estimates are used as analogues of univariate order statistics in procedures for extreme quantile estimation. The performance of the method is evaluated for both heavy tailed distributions and distributions with a finite right endpoint using a small sample simulation study. A bootstrap procedure is developed to guide in the selection of an optimal local bandwidth. Finally the procedure is illustrated in two case studies.
ISSN: 0094-9655
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Statistics Section
Quantitative Psychology and Individual Differences
× corresponding author
# (joint) last author

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