Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data R package LambertW version 0.6.9-2 CRAN Task View: Distributions (https://CRAN.R-project.org/view=Distributions) 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. The most useful 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. Software Depends: MASS, ggplot2, Imports: lamW (>= 1.3.0), stats, graphics, grDevices, RColorBrewer, reshape2, Rcpp (>= 1.0.4), methods LinkingTo: Rcpp, lamW Suggests: boot, Rsolnp, nortest, numDeriv, testthat, data.table, moments, knitr, markdown, vars, Georg M. Goerg <im@gmge.org> Comprehensive R Archive Network (CRAN) Georg M. Goerg [aut, cre] GPL (>= 2) 2025-08-21 application/tgz https://CRAN.R-project.org/package=LambertW doi:10.32614/CRAN.package.LambertW