Normality test package

Version 1.2.0.0 (8,65 ko) par Ipek
This function calculates p-values for ten well-known normality tests.
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Mise à jour 3 avr. 2018

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This function provides ten Normality tests that are not altogether available under one compact routine as a compiled Matlab function. All tests are coded to provide p-values for those normality tests, and the this function gives the results as an output table. Included tests are: Kolmogorov-Smirnov test (Limiting form (KS-Lim), Stephens Method (KS-S), Marsaglia Method (KS-M), Lilliefors test (KS-L)), Anderson-Darling (AD) test, Cramer-Von Mises (CvM) test, Shapiro-Wilk (SW) test, Shapiro-Francia (SF) test, Jarque-Bera (JB) test, D’Agostino and Pearson (DAP) test. Tests are not meant for big data. Most tests does not work for data bigger than 900. We are working on an improvement about this.

Citation pour cette source

Ipek (2025). Normality test package (https://fr.mathworks.com/matlabcentral/fileexchange/60147-normality-test-package), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2012b
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Version Publié le Notes de version
1.2.0.0

Please cite this as: Öner, M., & Deveci Kocakoç, İ. (2017). JMASM 49: A Compilation of Some Popular Goodness of Fit Tests for Normal Distribution: Their Algorithms and MATLAB Codes (MATLAB). Journal of Modern Applied Statistical Methods, 16(2), 30.
1.1.0.0

Names of the tests are included as a list.
Tests are not meant for big data. Most tests does not work for data bigger than 800. We are working on an improvement about this.
1.0.0.0