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. Probably the most important 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 <im@gmge.org> 
Date of publication  20160329 10:48:16 
Maintainer  Georg M. Goerg <im@gmge.org> 
License  GPL (>= 2) 
Version  0.6.4 
URL  http://www.gmge.org http://arxiv.org/abs/0912.4554 http://arxiv.org/abs/1010.2265 http://arxiv.org/abs/1602.02200 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.