sstn: Self-Similarity Test for Normality

Implements the Self-Similarity Test for Normality (SSTN), a new statistical test designed to assess whether a given sample originates from a normal distribution. The method exploits the self-similarity property of the normal characteristic function by iteratively transforming and comparing standardized empirical characteristic functions. The null distribution of the test statistic is obtained via Monte Carlo simulation. Details of the methodology are described in Anarat and Schwender (2026), "A test for normality based on self-similarity", <doi:10.48550/arXiv.2604.03810>.

Version: 1.0.1
Depends: R (≥ 3.5)
Imports: MASS
Suggests: knitr, rmarkdown
Published: 2026-04-11
DOI: 10.32614/CRAN.package.sstn
Author: Akin Anarat [aut, cre]
Maintainer: Akin Anarat <akin.anarat at hhu.de>
License: GPL-3
NeedsCompilation: no
Language: en-US
Materials: NEWS
CRAN checks: sstn results

Documentation:

Reference manual: sstn.html , sstn.pdf
Vignettes: Introduction to sstn (source, R code)

Downloads:

Package source: sstn_1.0.1.tar.gz
Windows binaries: r-devel: sstn_1.0.0.zip, r-release: sstn_1.0.0.zip, r-oldrel: sstn_1.0.0.zip
macOS binaries: r-release (arm64): sstn_1.0.0.tgz, r-oldrel (arm64): sstn_1.0.0.tgz, r-release (x86_64): sstn_1.0.1.tgz, r-oldrel (x86_64): sstn_1.0.1.tgz
Old sources: sstn archive

Linking:

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