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).
- Sprache
-
Englisch
- Erschienen in
-
Series: Diskussionspapier ; No. 73/2006
- Klassifikation
-
Wirtschaft
- Thema
-
Generalized kurtosis transformation
H-transformation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Fischer, Matthias J.
- Ereignis
-
Veröffentlichung
- (wer)
-
Friedrich-Alexander-Universität Erlangen-Nürnburg, Lehrstuhl für Statistik und Ökonometrie
- (wo)
-
Nürnberg
- (wann)
-
2006
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Fischer, Matthias J.
- Friedrich-Alexander-Universität Erlangen-Nürnburg, Lehrstuhl für Statistik und Ökonometrie
Entstanden
- 2006
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