Full metadata record
DC FieldValueLanguage
dc.contributor.authorKinsvater, Paul-
dc.contributor.authorFried, Roland-
dc.contributor.authorLilienthal, Jona-
dc.date.accessioned2015-06-29T12:28:42Z-
dc.date.available2015-06-29T12:28:42Z-
dc.date.issued2015-
dc.identifier.urihttp://hdl.handle.net/2003/34126-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-7513-
dc.description.abstractThis paper deals with inference on extremes of heavy tailed distributions. We assume distribution functions F of Pareto-type, i.e. 1-F(x)=x^-1/y L(x) for some γ> 0 and a slowly varying function L : ℝ_+→ℝ_+. Here, the so called extreme value index (EVI) γ is of key importance. In some applications observations from closely related variables are available, with possibly identical EVIγ . If these variables are observed for the same time period, a procedure called BEAR estimator has already been proposed. We modify this approach allowing for different observation periods and pairwise extreme value dependence of the variables. In addition, we present a new test for equality of the extreme value index. As an application, we discuss regional ood frequency analysis, where we want to combine rather short sequences of observations with very different lengths measured at many gauges for joint inference.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;20/2015en
dc.subjectHill estimatoren
dc.subjectregional ood frequency analysisen
dc.subjecthomogeneity testen
dc.subjectextreme value indexen
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.titleRegional extreme value index estimation and a test of homogeneityen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

Files in This Item:
File Description SizeFormat 
DP_2015_SFB823_Kinsvater_Fried_Lilienthal.pdfDNB459.73 kBAdobe PDFView/Open


This item is protected by original copyright



This item is protected by original copyright rightsstatements.org