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If you use 'LambertW' in your publication please cite the 'LambertW' R package as well as the Lambert W x F articles in Annals of Applied Statisics and / or The Scientific World Journal:

Goerg GM (2023). “LambertW: Probabilistic Models to Analyze and Gaussianize Heavy-Tailed, Skewed Data.” R package version 0.6.9-1.

Goerg GM (2011). “Lambert W random variables - a new family of generalized skewed distributions with applications to risk estimation.” Annals of Applied Statistics, 5(3), 2197-2230.

Goerg GM (2014). “The Lambert Way to Gaussianize heavy-tailed data with the inverse of Tukey's h transformation as a special case.” The Scientific World Journal: Special Issue on Probability and Statistics with Applications in Finance and Economics, ?(?), ??

Corresponding BibTeX entries:

  @Misc{,
    entry = {Manual},
    title = {LambertW: Probabilistic Models to Analyze and Gaussianize
      Heavy-Tailed, Skewed Data},
    author = {Georg M. Goerg},
    year = {2023},
    note = {R package version 0.6.9-1},
  }
  @Article{,
    entry = {article},
    title = {Lambert W random variables - a new family of generalized
      skewed distributions with applications to risk estimation},
    author = {Georg M. Goerg},
    year = {2011},
    journal = {Annals of Applied Statistics},
    volume = {5},
    number = {3},
    pages = {2197-2230},
  }
  @Article{,
    entry = {article},
    title = {The Lambert Way to Gaussianize heavy-tailed data with the
      inverse of Tukey's h transformation as a special case},
    author = {Georg M. Goerg},
    year = {2014},
    journal = {The Scientific World Journal: Special Issue on
      Probability and Statistics with Applications in Finance and
      Economics},
    volume = {?},
    number = {?},
    pages = {??},
  }

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.