Smoothed Block Empirical Likelihood for Quantiles of Weakly Dependent Processes Chen, Song Wong, Chiu
dc.contributor.department Statistics 2018-02-16T19:21:34.000 2020-07-02T06:56:13Z 2020-07-02T06:56:13Z 2006-08-01
dc.description.abstract <p>Inference on quantiles associated with dependent observation is a commonly encountered task in risk management these days. This paper considers employing the empirical likelihood to construct confidence intervals for quantiles of the stationary distribution of a weakly dependent process. To accommodate data dependence and avoid any secondary variance estimation, the empirical likelihood is formulated based on blocks of observations. To reduce the length of the confidence intervals, the weighted empirical distribution is smoothed by a kernel function and a smoothing bandwidth. It shows that a rescaled version of the smoothed block empirical likelihood ratio admits a limiting chi-square distribution with one degree of freedom, which facilitates likelihood ratio confidence intervals for the quantiles.</p>
dc.description.comments <p>This preprint was published as Song Xi Chen and Chiu Min Wong, " Smoothed Block Empirical Likelihood for Quantiles of Weakly Dependent Processes", <em>Statistica Sinica</em> (2009): 71-81.</p>
dc.identifier archive/
dc.identifier.articleid 1044
dc.identifier.contextkey 7343724
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_preprints/47
dc.language.iso en
dc.source.bitstream archive/|||Sat Jan 15 00:24:44 UTC 2022
dc.subject.disciplines Statistics and Probability
dc.subject.keywords alpha-mixing
dc.subject.keywords empirical likelihood
dc.subject.keywords kernel smoothing
dc.subject.keywords quantile
dc.subject.keywords Value-at-Risk
dc.subject.keywords Peking University
dc.title Smoothed Block Empirical Likelihood for Quantiles of Weakly Dependent Processes
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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