H_gamma

<p>skewness parameter; default <code>gamma = 0</code>, which implies
<code>H_gamma(u) = u</code>.</p>

gamma

<p>Skewed Lambert W\(\times\) F RV transformation: \(H_{\gamma}(u) = u
    \exp(\gamma u)\).</p>

math

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.

H_gamma: H transformation with gamma

Description

Usage

Arguments

Value

See Also