osktnorm
1.1.2A 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
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-03-184 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Documentation
- Examples that run
- 94%
- Documented parameters
- 98%
- Return-value docs
- 100%
- References docs
- 72%
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.1.2Latest2026-03-18 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-03-18
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 31 KB / 1 file
- Download size
- 791 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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