LambertW: Probabilistic Models to Analyze and Gaussianize Heavy-Tailed,
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.
||lamW (≥ 1.0.0), stats, graphics, grDevices, RColorBrewer, reshape2, Rcpp
||boot, Rsolnp, nortest, numDeriv, testthat, gsl, moments
||Georg M. Goerg
||Georg M. Goerg <im at gmge.org>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
||LambertW citation info