Normality test package

Version 1.2.0.0 (8.65 KB) by Ipek
This function calculates p-values for ten well-known normality tests.
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Updated 3 Apr 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.

Cite As

Ipek (2024). Normality test package (https://www.mathworks.com/matlabcentral/fileexchange/60147-normality-test-package), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2012b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
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