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Open AccessArticle

Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length

1
Mathematics and Informatics Center, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
2
Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
3
Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki 305-8568, Japan
4
Centro de Investigación Operativa, Universidad Miguel Hernández, Avda. de la Universidad s/n, 03202 Elche, Spain
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(7), 713; https://doi.org/10.3390/e21070713
Received: 15 June 2019 / Revised: 10 July 2019 / Accepted: 19 July 2019 / Published: 22 July 2019
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PDF [1105 KB, uploaded 22 July 2019]
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Abstract

We propose a method for generating surrogate data that preserves all the properties of ordinal patterns up to a certain length, such as the numbers of allowed/forbidden ordinal patterns and transition likelihoods from ordinal patterns into others. The null hypothesis is that the details of the underlying dynamics do not matter beyond the refinements of ordinal patterns finer than a predefined length. The proposed surrogate data help construct a test of determinism that is free from the common linearity assumption for a null-hypothesis. View Full-Text
Keywords: time series analysis; determinism; stochasticity; permutations; hypothesis testing time series analysis; determinism; stochasticity; permutations; hypothesis testing
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Hirata, Y.; Shiro, M.; Amigó, J.M. Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length. Entropy 2019, 21, 713.

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