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The Anderson-Darling test is a statistical test of whether a given sample of data is drawn from a given probability distribution. When applied to testing if a normal distribution adequately describes a set of data, it is one of the most powerful statistical tools for detecting most departures from normality.
For a normal distribution the Anderson-Darling statistic should take values close to 0.25.
References
Warnings
The original FATS documentation says that the result of AndersonDarling must be ~0.25 for gausian distribution but the result is ~-0.60
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Create plot routine for extractor
AndersonDarling
.Path: feets.extractors.ext_anderson_darling.py
Features
Extractor Documentation
The text was updated successfully, but these errors were encountered: