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The Lambert Way to Gaussianize Heavy-Tailed Data with the Inverse of Tukey’s h Transformation as a Special Case
Author
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-25
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
I present a parametric, bijective transformation to generate heavy tail versions of arbitrary random variables.
The tail behavior of this heavy tail Lambert W × F X random variable depends on a tail parameter δ ≥ 0 : for δ = 0 , Y ≡ X , for δ > 0 Y has heavier tails than X .
For X being Gaussian it reduces to Tukey’s h distribution.
The Lambert W function provides an explicit inverse transformation, which can thus remove heavy tails from observed data.
It also provides closed-form expressions for the cumulative distribution (cdf) and probability density function (pdf).
As a special case, these yield analytic expression for Tukey’s h pdf and cdf.
Parameters can be estimated by maximum likelihood and applications to S&P 500 log-returns demonstrate the usefulness of the presented methodology.
The R package LambertW implements most of the introduced methodology and is publiclyavailable on CRAN.
American Psychological Association (APA)
Goerg, Georg M.. 2015. The Lambert Way to Gaussianize Heavy-Tailed Data with the Inverse of Tukey’s h Transformation as a Special Case. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1079277
Modern Language Association (MLA)
Goerg, Georg M.. The Lambert Way to Gaussianize Heavy-Tailed Data with the Inverse of Tukey’s h Transformation as a Special Case. The Scientific World Journal No. 2015 (2015), pp.1-16.
https://search.emarefa.net/detail/BIM-1079277
American Medical Association (AMA)
Goerg, Georg M.. The Lambert Way to Gaussianize Heavy-Tailed Data with the Inverse of Tukey’s h Transformation as a Special Case. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-16.
https://search.emarefa.net/detail/BIM-1079277
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1079277