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

Autor: Yoshito Hirata, Masanori Shiro, José M. Amigó
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Entropy, Vol 21, Iss 7, p 713 (2019)
Druh dokumentu: article
ISSN: 1099-4300
DOI: 10.3390/e21070713
Popis: 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.
Databáze: Directory of Open Access Journals
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