LambertW (0.5.1)

Analyze and Gaussianize Heavy-Tailed, Skewed Data.

http://www.gmge.org http://arxiv.org/abs/0912.4554 http://arxiv.org/abs/1010.2265
http://cran.r-project.org/web/packages/LambertW

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.

Maintainer: Georg M. Goerg
Author(s): Georg M. Goerg <im@gmge.org>

License: GPL (>= 2)

Uses: gsl, MASS, moments, nortest, numDeriv, Rsolnp
Reverse depends: LindleyR, SpatialVx

Released almost 5 years ago.