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dc.contributor.authorLee, David
dc.contributor.authorJoe, Harry
dc.contributor.authorKrupskii, Pavel
dc.date.accessioned2018-01-01T12:19:02Z
dc.date.available2018-01-01T12:19:02Z
dc.date.issued2017-12-02
dc.identifier.citationLee D, Joe H, Krupskii P (2017) Tail-weighted dependence measures with limit being the tail dependence coefficient. Journal of Nonparametric Statistics: 1–29. Available: http://dx.doi.org/10.1080/10485252.2017.1407414.
dc.identifier.issn1048-5252
dc.identifier.issn1029-0311
dc.identifier.doi10.1080/10485252.2017.1407414
dc.identifier.urihttp://hdl.handle.net/10754/626608
dc.description.abstractFor bivariate continuous data, measures of monotonic dependence are based on the rank transformations of the two variables. For bivariate extreme value copulas, there is a family of estimators (Formula presented.), for (Formula presented.), of the extremal coefficient, based on a transform of the absolute difference of the α power of the ranks. In the case of general bivariate copulas, we obtain the probability limit (Formula presented.) of (Formula presented.) as the sample size goes to infinity and show that (i) (Formula presented.) for (Formula presented.) is a measure of central dependence with properties similar to Kendall's tau and Spearman's rank correlation, (ii) (Formula presented.) is a tail-weighted dependence measure for large α, and (iii) the limit as (Formula presented.) is the upper tail dependence coefficient. We obtain asymptotic properties for the rank-based measure (Formula presented.) and estimate tail dependence coefficients through extrapolation on (Formula presented.). A data example illustrates the use of the new dependence measures for tail inference.
dc.description.sponsorshipThe authors would like to thank the anonymous referees for their useful comments and suggestions.
dc.publisherInforma UK Limited
dc.relation.urlhttp://www.tandfonline.com/doi/full/10.1080/10485252.2017.1407414
dc.subjectCopula
dc.subjectextremal coefficient
dc.subjectmonotone dependence
dc.subjecttail order
dc.subjecttail-weighted dependence
dc.titleTail-weighted dependence measures with limit being the tail dependence coefficient
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalJournal of Nonparametric Statistics
dc.contributor.institutionDepartment of Statistics, University of British Columbia, Vancouver, British Columbia, Canada
kaust.personKrupskiy, Pavel
dc.date.published-online2017-12-02
dc.date.published-print2018-04-03


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