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dc.contributor.authorFischer, Matthias J.en
dc.date.accessioned2009-12-02-
dc.date.accessioned2010-01-13T14:06:14Z-
dc.date.available2010-01-13T14:06:14Z-
dc.date.issued2006-
dc.identifier.urihttp://hdl.handle.net/10419/29570-
dc.description.abstractOne possibility to construct heavy tail distributions is to directly manipulate a standard Gaussian random variable by means of transformations which satisfy certain conditions. This approach dates back to Tukey (1960) who introduces the popular H-transformation. Alternatively, the K-transformation of MacGillivray & Cannon (1997) or the J-transformation of Fischer & Klein (2004) may be used. Recently, Klein & Fischer (2006) proposed a very general power kurtosis transformation which includes the above-mentioned transformations as special cases. Unfortunately, their transformation requires an infinite number of unknown parameters to be estimated. In contrast, we introduce a very simple method to construct êexible kurtosis transformations. In particular, manageable superstructures are suggested in order to statistically discriminate between H-, J-and K-distributions (associated to H-, J- and K-transformations).en
dc.language.isoengen
dc.publisher|aFriedrich-Alexander-Universität Erlangen-Nürnburg, Lehrstuhl für Statistik und Ökonometrie |cNürnbergen
dc.relation.ispartofseries|aDiskussionspapier |x73/2006en
dc.subject.ddc330en
dc.subject.keywordGeneralized kurtosis transformationen
dc.subject.keywordH-transformationen
dc.titleA note on the construction of generalized Tukey-type transformations-
dc.type|aWorking Paperen
dc.identifier.ppn614054869en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:faucse:732006en

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