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dc.contributor.authorDupuis, D. J.
dc.contributor.authorSun, Ying
dc.contributor.authorWang, Huixia Judy
dc.date.accessioned2015-04-29T13:25:42Z
dc.date.available2015-04-29T13:25:42Z
dc.date.issued2015-02-13
dc.identifier.citationDetecting change-points in extremes 2015, 8 (1):19 Statistics and Its Interface
dc.identifier.issn19387989
dc.identifier.issn19387997
dc.identifier.doi10.4310/SII.2015.v8.n1.a3
dc.identifier.urihttp://hdl.handle.net/10754/550889
dc.description.abstractEven though most work on change-point estimation focuses on changes in the mean, changes in the variance or in the tail distribution can lead to more extreme events. In this paper, we develop a new method of detecting and estimating the change-points in the tail of multiple time series data. In addition, we adapt existing tail change-point detection methods to our specific problem and conduct a thorough comparison of different methods in terms of performance on the estimation of change-points and computational time. We also examine three locations on the U.S. northeast coast and demonstrate that the methods are useful for identifying changes in seasonally extreme warm temperatures.
dc.publisherInternational Press of Boston
dc.relation.urlhttp://www.intlpress.com/site/pub/pages/journals/items/sii/content/vols/0008/0001/a003/
dc.rightsArchived with thanks to Statistics and Its Interface
dc.subjecttail behavior
dc.subjectquantile methods
dc.titleDetecting change-points in extremes
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentEnvironmental Statistics Group
dc.contributor.departmentStatistics Program
dc.identifier.journalStatistics and Its Interface
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionDepartment of Management Sciences, HEC Montréal, Québec, Canada
dc.contributor.institutionDepartment of Statistics, Ohio State University, Columbus, Oh., U.S.A.
dc.contributor.institutionDepartment of Statistics, George Washington University, Washington, D.C., U.S.A.
kaust.personSun, Ying
refterms.dateFOA2018-06-13T18:01:06Z
dc.date.published-online2015-02-13
dc.date.published-print2015


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