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

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 under...

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Detalles Bibliográficos
Autores principales: Hirata, Yoshito, Shiro, Masanori, Amigó, José M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515228/
https://www.ncbi.nlm.nih.gov/pubmed/33267427
http://dx.doi.org/10.3390/e21070713
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author Hirata, Yoshito
Shiro, Masanori
Amigó, José M.
author_facet Hirata, Yoshito
Shiro, Masanori
Amigó, José M.
author_sort Hirata, Yoshito
collection PubMed
description 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.
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spelling pubmed-75152282020-11-09 Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length Hirata, Yoshito Shiro, Masanori Amigó, José M. Entropy (Basel) Article 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. MDPI 2019-07-22 /pmc/articles/PMC7515228/ /pubmed/33267427 http://dx.doi.org/10.3390/e21070713 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hirata, Yoshito
Shiro, Masanori
Amigó, José M.
Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length
title Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length
title_full Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length
title_fullStr Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length
title_full_unstemmed Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length
title_short Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length
title_sort surrogate data preserving all the properties of ordinal patterns up to a certain length
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515228/
https://www.ncbi.nlm.nih.gov/pubmed/33267427
http://dx.doi.org/10.3390/e21070713
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AT amigojosem surrogatedatapreservingallthepropertiesofordinalpatternsuptoacertainlength

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