文章基本信息

标题：Nonparametric inference for extremal conditional quantiles
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作者：Daisuke Kurisu ; Taisuke Otsu
期刊名称：Distributional Analysis Publications
印刷版ISSN：1352-2469
出版年度：2021
卷号：2021
页码：1-28
语种：English
出版社：Suntory Toyota International Centres for Economics and Related Disciplines
摘要：This paper studies asymptotic properties of the local linear quantile estimator under the extremal order quantile asymptotics, and develops a practical inference method for conditional quantiles in extreme tail areas. By using a point process technique, the asymptotic distribution of the local linear quantile estimator is derived as a minimizer of certain functional of a Poisson point process that involves nuisance parameters. To circumvent difficulty of estimating those nuisance parameters, we propose a subsampling inference method for conditional extreme quantiles based on a self-normalized version of the local linear estimator. A simulation study illustrates usefulness of our subsampling inference to investigate extremal phenomena.
关键词：quantile regression;extreme value theory;point process;subsampling