Lambert W x F distributions are a generalized framework to analyze skewed, heavy-tailed data. It is based on an input/output system, where the output random variable (RV) Y is a non-linearly transformed version of an input RV X ~ F with similar properties as X, but slightly skewed (heavy-tailed). The 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.

Documentation

Manual: LambertW.pdf
Vignette: None available.

Maintainer: Georg M. Goerg <im at gmge.org>

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

Install package and any missing dependencies by running this line in your R console:

install.packages("LambertW")

Depends MASS, ggplot2,
Imports lamW(>=1.0.0), stats, graphics, grDevices, RColorBrewer, reshape2, Rcpp
Suggests boot, Rsolnp, nortest, numDeriv, testthat, moments,
Enhances
Linking to Rcpp, lamW
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CryptRndTest, optband
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Package LambertW
Materials
URL http://www.gmge.org http://arxiv.org/abs/0912.4554 http://arxiv.org/abs/1010.2265 http://arxiv.org/abs/1602.02200
Task Views Distributions
Version 0.6.4
Published 2016-03-29
License GPL (>= 2)
BugReports
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks LambertW check results
Package source LambertW_0.6.4.tar.gz