osktnorm
A Moment-Targeting Normality Transformation Based on Tukey g-h Distribution
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.2 |
rolling linux/jammy R-4.5 | osktnorm_1.1.2.tar.gz |
930.8 KiB |
1.1.2 |
rolling linux/noble R-4.5 | osktnorm_1.1.2.tar.gz |
932.0 KiB |
1.1.2 |
rolling source/ R- | osktnorm_1.1.2.tar.gz |
788.9 KiB |
1.1.2 |
latest linux/jammy R-4.5 | osktnorm_1.1.2.tar.gz |
930.8 KiB |
1.1.2 |
latest linux/noble R-4.5 | osktnorm_1.1.2.tar.gz |
932.0 KiB |
1.1.2 |
latest source/ R- | osktnorm_1.1.2.tar.gz |
788.9 KiB |
1.1.2 |
2026-04-26 source/ R- | osktnorm_1.1.2.tar.gz |
788.9 KiB |
1.1.2 |
2026-04-23 source/ R- | osktnorm_1.1.2.tar.gz |
788.9 KiB |
1.1.2 |
2026-04-09 windows/windows R-4.5 | osktnorm_1.1.2.zip |
1.2 MiB |