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osktnorm

A Moment-Targeting Normality Transformation Based on Tukey g-h Distribution

v1.1.2 · Mar 17, 2026 · GPL (>= 2)

Description

Implements a moment-targeting normality transformation based on the simultaneous optimization of Tukey g-h distribution parameters. The method is designed to minimize both asymmetry (skewness) and excess peakedness (kurtosis) in non-normal data by mapping it to a standard normal distribution Cebeci et al (2026) <doi:10.3390/sym18030458>. Optimization is performed by minimizing an objective function derived from the Anderson-Darling goodness-of-fit statistic with Stephens's correction factor, utilizing the L-BFGS-B algorithm for robust parameter estimation. This approach provides an effective alternative to power transformations like Box-Cox and Yeo-Johnson, particularly for data requiring precise tail-behavior adjustment.

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OK 12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Apr 25, 2026
ERROR 4 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Mar 17, 2026
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Version History

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new 1.1.2 Mar 17, 2026