@techreport{Fischer2006note,
abstract = {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 \^{e}exible 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).},
address = {N\"{u}rnberg},
author = {Matthias J. Fischer},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {330; Generalized kurtosis transformation; H-transformation},
language = {eng},
number = {73/2006},
publisher = {Universit\"{a}t Erlangen-N\"{u}rnberg, Lehrstuhl f\"{u}r Statistik und empirische Wirtschaftsforschung},
title = {A note on the construction of generalized Tukey-type transformations},
type = {Diskussionspapiere // Friedrich-Alexander-Universit\"{a}t Erlangen-N\"{u}rnberg, Lehrstuhl f\"{u}r Statistik und \"{O}konometrie},
url = {http://hdl.handle.net/10419/29570},
year = {2006}
}
