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Revisiting detrended fluctuation analysis

Half a century ago Hurst introduced Rescaled Range (R/S) Analysis to study fluctuations in time series. Thousands of works have investigated or applied the original methodology and similar techniques, with Detrended Fluctuation Analysis becoming preferred due to its purported ability to mitigate non...

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Detalles Bibliográficos
Autores principales: Bryce, R. M., Sprague, K. B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303145/
https://www.ncbi.nlm.nih.gov/pubmed/22419991
http://dx.doi.org/10.1038/srep00315
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author Bryce, R. M.
Sprague, K. B.
author_facet Bryce, R. M.
Sprague, K. B.
author_sort Bryce, R. M.
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description Half a century ago Hurst introduced Rescaled Range (R/S) Analysis to study fluctuations in time series. Thousands of works have investigated or applied the original methodology and similar techniques, with Detrended Fluctuation Analysis becoming preferred due to its purported ability to mitigate nonstationaries. We show Detrended Fluctuation Analysis introduces artifacts for nonlinear trends, in contrast to common expectation, and demonstrate that the empirically observed curvature induced is a serious finite-size effect which will always be present. Explicit detrending followed by measurement of the diffusional spread of a signals' associated random walk is preferable, a surprising conclusion given that Detrended Fluctuation Analysis was crafted specifically to replace this approach. The implications are simple yet sweeping: there is no compelling reason to apply Detrended Fluctuation Analysis as it 1) introduces uncontrolled bias; 2) is computationally more expensive than the unbiased estimator; and 3) cannot provide generic or useful protection against nonstationaries.
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spelling pubmed-33031452012-03-14 Revisiting detrended fluctuation analysis Bryce, R. M. Sprague, K. B. Sci Rep Article Half a century ago Hurst introduced Rescaled Range (R/S) Analysis to study fluctuations in time series. Thousands of works have investigated or applied the original methodology and similar techniques, with Detrended Fluctuation Analysis becoming preferred due to its purported ability to mitigate nonstationaries. We show Detrended Fluctuation Analysis introduces artifacts for nonlinear trends, in contrast to common expectation, and demonstrate that the empirically observed curvature induced is a serious finite-size effect which will always be present. Explicit detrending followed by measurement of the diffusional spread of a signals' associated random walk is preferable, a surprising conclusion given that Detrended Fluctuation Analysis was crafted specifically to replace this approach. The implications are simple yet sweeping: there is no compelling reason to apply Detrended Fluctuation Analysis as it 1) introduces uncontrolled bias; 2) is computationally more expensive than the unbiased estimator; and 3) cannot provide generic or useful protection against nonstationaries. Nature Publishing Group 2012-03-14 /pmc/articles/PMC3303145/ /pubmed/22419991 http://dx.doi.org/10.1038/srep00315 Text en Copyright © 2012, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Article
Bryce, R. M.
Sprague, K. B.
Revisiting detrended fluctuation analysis
title Revisiting detrended fluctuation analysis
title_full Revisiting detrended fluctuation analysis
title_fullStr Revisiting detrended fluctuation analysis
title_full_unstemmed Revisiting detrended fluctuation analysis
title_short Revisiting detrended fluctuation analysis
title_sort revisiting detrended fluctuation analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303145/
https://www.ncbi.nlm.nih.gov/pubmed/22419991
http://dx.doi.org/10.1038/srep00315
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