Testing for General Dynamical Stationarity with a Symbolic Data Compression Technique

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dc.creatorKennel, Matthew B.
dc.creatorMees, Alistair I.
dc.date1998-12-23
dc.date.accessioned2026-07-07T02:35:37Z
dc.date.available2026-07-07T02:35:37Z
dc.descriptionWe construct a statistic and null test for examining the stationarity of time-series of discrete symbols: whether two data streams appear to originate from the same underlying unknown dynamical system, and if any difference is statistically significant. Using principles and computational techniques from the theory of data compression, the method intelligently accounts for the substantial serial correlation and nonlinearity found in realistic dynamical data, problems which bedevil naive methods. Symbolic methods are computationally efficient and robust to noise. We demonstrate the method on a number of realistic experimental datasets.
dc.descriptionIsaac Newton Institute Preprint, 1998
dc.identifierhttps://arxiv.org/abs/chao-dyn/9812030
dc.identifierhttp://arxiv.org/abs/chao-dyn/9812030
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/15673
dc.subjectChaotic Dynamics
dc.titleTesting for General Dynamical Stationarity with a Symbolic Data Compression Technique
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