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dc.contributor.authorCai, Zongwu
dc.date.accessioned2015-01-23T19:05:10Z
dc.date.available2015-01-23T19:05:10Z
dc.date.issued2002-02-01
dc.identifier.citationCai, Zongwu. (2002). "Regression quantiles for time series." Econometric Theory, 18(1):169-192. http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=92739&fulltextType=RA&fileId=S0266466602181096en_US
dc.identifier.issn0266-4666
dc.identifier.urihttp://hdl.handle.net/1808/16365
dc.descriptionThis is the publisher's version, also available electronically from http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=92739&fulltextType=RA&fileId=S0266466602181096.en_US
dc.description.abstractIn this paper we study nonparametric estimation of regression quantiles for time series data by inverting a weighted Nadaraya–Watson (WNW) estimator of conditional distribution function, which was first used by Hall, Wolff, and Yao (1999, Journal of the American Statistical Association 94, 154–163). First, under some regularity conditions, we establish the asymptotic normality and weak consistency of the WNW conditional distribution estimator for [alpha]-mixing time series at both boundary and interior points, and we show that the WNW conditional distribution estimator not only preserves the bias, variance, and, more important, automatic good boundary behavior properties of local linear “double-kernel” estimators introduced by Yu and Jones (1998, Journal of the American Statistical Association 93, 228–237), but also has the additional advantage of always being a distribution itself. Second, it is shown that under some regularity conditions, the WNW conditional quantile estimator is weakly consistent and normally distributed and that it inherits all good properties from the WNW conditional distribution estimator. A small simulation study is carried out to illustrate the performance of the estimates, and a real example is also used to demonstrate the methodology.en_US
dc.publisherCambridge University Pressen_US
dc.relation.isversionofhttp://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=92739&fulltextType=RA&fileId=S0266466602181096en_US
dc.titleRegression quantiles for time seriesen_US
dc.typeArticle
kusw.kuauthorCai, Zhongwu
kusw.kudepartmentEconomicsen_US
kusw.oaversionScholarly/refereed, publisher version
kusw.oapolicyThis item does not meet KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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