A Moment-Targeting Normality Transformation Based on Tukey g-h Distribution
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK12 OK2026-04-25
- ERROR4 OK, 1 ERROR2026-03-18
Documentation
- Help pages
- 18
- Examples that run
- 94%17 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 98%
- Return-value docs
- 100%
- Help pages citing references
- 72%
Downloads
Dependencies
Installing osktnorm adds 8 packages (3 with compiled code, 4.3 MB of source tarballs). Heaviest: Rcpp 1.8 MB, vioplot 725 KB, zoo 675 KB.
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- 1.1.2Latest2026-03-17 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-03-17
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 31 KB / 1 file
- Download size
- 791 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("osktnorm")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.3390/sym18030458.
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