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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.