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Visual information and expert’s idea in Hurst index estimation of the fractional Brownian motion using a diffusion type approximation
An approximation of the fractional Brownian motion based on the Ornstein-Uhlenbeck process is used to obtain an asymptotic likelihood function. Two estimators of the Hurst index are then presented in the likelihood approach. The first estimator is produced according to the observed values of the sam...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5307349/ https://www.ncbi.nlm.nih.gov/pubmed/28195153 http://dx.doi.org/10.1038/srep42482 |
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author | Taheriyoun, Ali R. Moghimbeygi, Meisam |
author_facet | Taheriyoun, Ali R. Moghimbeygi, Meisam |
author_sort | Taheriyoun, Ali R. |
collection | PubMed |
description | An approximation of the fractional Brownian motion based on the Ornstein-Uhlenbeck process is used to obtain an asymptotic likelihood function. Two estimators of the Hurst index are then presented in the likelihood approach. The first estimator is produced according to the observed values of the sample path; while the second one employs the likelihood function of the incremental process. We also employ visual roughness of realization to restrict the parameter space and to obtain prior information in Bayesian approach. The methods are then compared with three contemporary estimators and an experimental data set is studied. |
format | Online Article Text |
id | pubmed-5307349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53073492017-02-22 Visual information and expert’s idea in Hurst index estimation of the fractional Brownian motion using a diffusion type approximation Taheriyoun, Ali R. Moghimbeygi, Meisam Sci Rep Article An approximation of the fractional Brownian motion based on the Ornstein-Uhlenbeck process is used to obtain an asymptotic likelihood function. Two estimators of the Hurst index are then presented in the likelihood approach. The first estimator is produced according to the observed values of the sample path; while the second one employs the likelihood function of the incremental process. We also employ visual roughness of realization to restrict the parameter space and to obtain prior information in Bayesian approach. The methods are then compared with three contemporary estimators and an experimental data set is studied. Nature Publishing Group 2017-02-14 /pmc/articles/PMC5307349/ /pubmed/28195153 http://dx.doi.org/10.1038/srep42482 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Taheriyoun, Ali R. Moghimbeygi, Meisam Visual information and expert’s idea in Hurst index estimation of the fractional Brownian motion using a diffusion type approximation |
title | Visual information and expert’s idea in Hurst index estimation of the fractional Brownian motion using a diffusion type approximation |
title_full | Visual information and expert’s idea in Hurst index estimation of the fractional Brownian motion using a diffusion type approximation |
title_fullStr | Visual information and expert’s idea in Hurst index estimation of the fractional Brownian motion using a diffusion type approximation |
title_full_unstemmed | Visual information and expert’s idea in Hurst index estimation of the fractional Brownian motion using a diffusion type approximation |
title_short | Visual information and expert’s idea in Hurst index estimation of the fractional Brownian motion using a diffusion type approximation |
title_sort | visual information and expert’s idea in hurst index estimation of the fractional brownian motion using a diffusion type approximation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5307349/ https://www.ncbi.nlm.nih.gov/pubmed/28195153 http://dx.doi.org/10.1038/srep42482 |
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