LambertW (0.6.2)

Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data.

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.

Maintainer: Georg M. Goerg
Author(s): Georg M. Goerg <>

License: GPL (>= 2)

Uses: ggplot2, lamW, MASS, RColorBrewer, Rcpp, reshape2, boot, gsl, moments, nortest, numDeriv, testthat, Rsolnp
Reverse depends: LindleyR, SpatialVx

Released about 4 years ago.