LambertW: Analyze and Gaussianize Heavy-Tailed, Skewed Data
Lambert W x F distributions are a generalized framework to analyze
skewed, heavy-tailed data. They are based on an input/output system, where
the input random variable (RV) X ~ F, and the output Y is a non-linearly
transformed version of X with similar properties, but slightly skewed and/or
heavy-tailed. This transformed RV Y has a Lambert W x F distribution.
This package contains functions to model and analyze skewed, heavy-tailed
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 do-it-yourself toolkit allows users to define
their own Lambert W x 'MyFavoriteDistribution' and use it in their analysis
right away.
Downloads:
Reverse dependencies: