The Lambert Way to Gaussianize Heavy-Tailed Data with the Inverse of Tukey’s h Transformation as a Special Case
I present a parametric, bijective transformation to generate heavy tail versions of arbitrary random variables. The tail behavior of this heavy tail Lambert W × FX 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 t...
Saved in:
| Main Author: | Georg M. Goerg |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
|
| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/909231 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
New Inversion Formulae for the Widder–Lambert and Stieltjes–Poisson Transforms
by: Emilio R. Negrín, et al.
Published: (2025-04-01) -
Overcoming challenges in prevalence meta-analysis: the case for the Freeman-Tukey transform
by: Jazeel Abdulmajeed, et al.
Published: (2025-04-01) -
A Mixture of Generalized Tukey’s g Distributions
by: José Alfredo Jiménez, et al.
Published: (2016-01-01) -
An empirical assessment of Tukey combined extended exponentially weighted moving average control chart
by: Khanittha Talordphop, et al.
Published: (2025-02-01) -
Application of the Heavy-tailed Estimation in Financial Data
by: CHEN Hai-long, et al.
Published: (2019-04-01)