Arbeitspapier
A note on the construction of generalized Tukey-type transformations
One 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).
- Language
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Englisch
- Bibliographic citation
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Series: Diskussionspapier ; No. 73/2006
- Classification
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Wirtschaft
- Subject
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Generalized kurtosis transformation
H-transformation
- Event
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Geistige Schöpfung
- (who)
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Fischer, Matthias J.
- Event
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Veröffentlichung
- (who)
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Friedrich-Alexander-Universität Erlangen-Nürnburg, Lehrstuhl für Statistik und Ökonometrie
- (where)
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Nürnberg
- (when)
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2006
- Handle
- Last update
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10.03.2025, 11:45 AM CET
Data provider
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Object type
- Arbeitspapier
Associated
- Fischer, Matthias J.
- Friedrich-Alexander-Universität Erlangen-Nürnburg, Lehrstuhl für Statistik und Ökonometrie
Time of origin
- 2006
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