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Analyze and Gaussianize skewed, heavy-tailed data
Georg M. Goerg <>
GPL (>= 2)
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.
Package Version Released
LambertW 3 years 11 weeks ago
LambertW 3 years 43 weeks ago
LambertW 0.2.9 3 years 46 weeks ago
LambertW 0.2.6 4 years 11 weeks ago
LambertW 0.2.5 4 years 12 weeks ago
LambertW 0.1.9 5 years 11 weeks ago
LambertW 0.1.8 5 years 13 weeks ago
LambertW 0.1.6
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