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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 procedure is based on iteratively estimating the characteristic function of the sum of standardized i.i.d. random variables and comparing it to the characteristic function of the standard normal distribution. A Monte Carlo procedure is used to determine the empirical distribution of the test statistic under the null hypothesis. Details of the methodology are described in Anarat and Schwender (2025), "A normality test based on self-similarity" (Submitted).
| Version: | 1.0.0 |
| Suggests: | knitr, rmarkdown |
| Published: | 2025-09-16 |
| 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 |
| CRAN checks: | sstn results |
| Reference manual: | sstn.html , sstn.pdf |
| Vignettes: |
Introduction to sstn (source, R code) |
| Package source: | sstn_1.0.0.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_1.0.0.tgz, r-oldrel (x86_64): sstn_1.0.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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