Lambert W x F distributions are a generalized framework to analyze skewed, heavytailed data. It is based on an input/output system, where the output random variable (RV) Y is a nonlinearly transformed version of an input RV X ~ F with similar properties as X, but slightly skewed (heavytailed). The transformed RV Y has a Lambert W x F distribution. This package contains functions to model and analyze skewed, heavytailed data the Lambert Way: simulate random samples, estimate parameters, compute quantiles, and plot/ print results nicely. The most useful function is 'Gaussianize', which works similarly to 'scale', but actually makes the data Gaussian. A doityourself toolkit allows users to define their own Lambert W x 'MyFavoriteDistribution' and use it in their analysis right away.
Package details 


Author  Georg M. Goerg [aut, cre] 
Maintainer  Georg M. Goerg <im@gmge.org> 
License  GPL (>= 2) 
Version  0.6.71 
URL  https://github.com/gmgeorg/LambertW https://arxiv.org/abs/0912.4554 https://arxiv.org/abs/1010.2265 https://arxiv.org/abs/1602.02200 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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