swMATH ID: 6066
Software Authors: Georg M. Goerg
Description: LambertW: Analyze and Gaussianize skewed, heavy-tailed data , The Lambert W framework is a new generalized way to analyze skewed, heavy-tailed data. Lambert W random variables (RV) are based on an input/output framework where the input is a RV X with distribution F(x), and the output Y = func(X) has similar properties as X (but slightly skewed or heavy-tailed). Then this transformed RV Y has a Lambert W x F distribution - for details see References. This package contains functions to perform a Lambert W analysis of skewed and heavy-tailed data: data can be simulated, parameters can be estimated from real world data, quantiles can be computed, and results plotted/printed in a ’nice’ way. Probably the most important function is ’Gaussianize’, which works the same way as the R function ’scale’ but actually makes your data Gaussian. An optional modular toolkit implementation allows users to define their own Lambert W x ’my favorite distribution’ and use it for their analysis.
Homepage: http://cran.r-project.org/web/packages/LambertW/
Source Code:  https://github.com/cran/LambertW
Dependencies: R; moments, gsl, MASS, nortest, maxLik
Keywords: family of skewed distributions; skewness; transformation of random variables; Lambert \(W\); latent variables; stylized facts of asset returns; value at risk; GARCH
Related Software: R; DLMF; CRAN; EnvStats; EnviroStat; MVN; MESgenCov; rfPermute; relaimpo; COUNT; pscl; MASS (R); LAMBERTW; wrightOmegaq; LambertW; LambertW; Algorithm 443; lamW; GitHub; Algorithm 917
Cited in: 12 Publications

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