LambertW: 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. 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.
| Version: |
0.6.9-2 |
| 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 |
| Published: |
2025-08-21 |
| DOI: |
10.32614/CRAN.package.LambertW |
| Author: |
Georg M. Goerg [aut, cre] |
| Maintainer: |
Georg M. Goerg <im at gmge.org> |
| BugReports: |
https://github.com/gmgeorg/LambertW/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/gmgeorg/LambertW,
https://arxiv.org/abs/0912.4554,
https://arxiv.org/abs/1010.2265,
https://arxiv.org/abs/1602.02200 |
| NeedsCompilation: |
yes |
| Citation: |
LambertW citation info |
| Materials: |
README, NEWS |
| In views: |
Distributions |
| CRAN checks: |
LambertW results |
Documentation:
Downloads:
Reverse dependencies:
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