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Stationarity test

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The stationarity of a time series is evaluated by using the reverse arrangement test.



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The reverse arrangement test was first introduced by [1]. The following examples are directly inspired from [2] and [3] where the stationarity of a signal is investigated. More specifically, the test evaluates the existence of a non-negligible trend. Only the 95% confidence interval is used here. All the credit go to the authors for the original methods.
[1] Julius S. Bendat, Allan G. Piersol, Random Data: Analysis and Measurement Procedures, 4th Edition; ISBN: 978-0-470-24877-5
[2] Homayon Aryan, Keith Yearby, Michael Balikhin, Oleksiy Agapitov, Vladimir Krasnoselskikh, Richard Boynton, Statistical study of chorus wave distributions in the inner magnetosphere usingAeand solar wind parameters, Journal of Geophysical Research: Space Physics, 2014, 119, 8, 6131
[3] Travis W. Beck, Terry J. Housh, Joseph P. Weir, Joel T. Cramer, Vassilios Vardaxis, Glen O. Johnson, Jared W. Coburn, Moh H. Malek, Michelle Mielke, An examination of the Runs Test, Reverse Arrangements Test, and modified Reverse Arrangements Test for assessing surface EMG signal stationarity, Journal of Neuroscience Methods, Volume 156, Issues 1–2, 30 September 2006, Pages 242-248, ISSN 0165-0270,

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function description + some debugging




-doi updated


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