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.

Version: 0.5
Depends: moments, MASS
Imports: gsl
Suggests: Rsolnp, nortest, numDeriv
Published: 2014-11-22
Author: Georg M. Goerg
Maintainer: Georg M. Goerg <im at gmge.org>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.gmge.org http://arxiv.org/abs/0912.4554 http://arxiv.org/abs/1010.2265
NeedsCompilation: no
Citation: LambertW citation info
Materials: NEWS
In views: Distributions
CRAN checks: LambertW results

Downloads:

Reference manual: LambertW.pdf
Package source: LambertW_0.5.tar.gz
Windows binaries: r-devel: LambertW_0.5.zip, r-release: LambertW_0.5.zip, r-oldrel: LambertW_0.5.zip
OS X Snow Leopard binaries: r-release: LambertW_0.5.tgz, r-oldrel: LambertW_0.5.tgz
OS X Mavericks binaries: r-release: not available
Old sources: LambertW archive