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dc.contributor.author
Shao, Ying-Hui
dc.contributor.author
Gu, Gao-Feng
dc.contributor.author
Jiang, Zhi-Qiang
dc.contributor.author
Zhou, Wei-Xing
dc.contributor.author
Sornette, Didier
dc.date.accessioned
2018-09-10T15:25:19Z
dc.date.available
2017-06-10T11:33:09Z
dc.date.available
2018-09-10T15:25:19Z
dc.date.issued
2012-11-12
dc.identifier.other
10.1038/srep00835
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/59162
dc.identifier.doi
10.3929/ethz-b-000059162
dc.description.abstract
Notwithstanding the significant efforts to develop estimators of long-range correlations (LRC) and to compare their performance, no clear consensus exists on what is the best method and under which conditions. In addition, synthetic tests suggest that the performance of LRC estimators varies when using different generators of LRC time series. Here, we compare the performances of four estimators [Fluctuation Analysis (FA), Detrended Fluctuation Analysis (DFA), Backward Detrending Moving Average (BDMA), and Centred Detrending Moving Average (CDMA)]. We use three different generators [Fractional Gaussian Noises, and two ways of generating Fractional Brownian Motions]. We find that CDMA has the best performance and DFA is only slightly worse in some situations, while FA performs the worst. In addition, CDMA and DFA are less sensitive to the scaling range than FA. Hence, CDMA and DFA remain “The Methods of Choice” in determining the Hurst index of time series.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Nature Publishing Group
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subject
Information theory and computation
en_US
dc.subject
Statistical physics, thermodynamics and nonlinear dynamics
en_US
dc.subject
Statistics
en_US
dc.subject
Software
en_US
dc.title
Comparing the performance of FA, DFA and DMA using different synthetic long-range correlated time series
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported
ethz.journal.title
Scientific Reports
ethz.journal.volume
2
en_US
ethz.pages.start
835
en_US
ethz.size
5 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.identifier.nebis
006751867
ethz.publication.place
London
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03738 - Sornette, Didier / Sornette, Didier
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03738 - Sornette, Didier / Sornette, Didier
ethz.date.deposited
2017-06-10T11:34:21Z
ethz.source
ECIT
ethz.identifier.importid
imp5936500aaec4946504
ethz.ecitpid
pub:94670
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-18T11:36:48Z
ethz.rosetta.lastUpdated
2019-01-02T13:51:54Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=Comparing%20the%20performance%20of%20FA,%20DFA%20and%20DMA%20using%20different%20synthetic%20long-range%20correlated%20time%20series&rft.jtitle=Scientific%20Reports&rft.date=2012-11-12&rft.volume=2&rft.spage=835&rft.au=Shao,%20Ying-Hui&Gu,%20Gao-Feng&Jiang,%20Zhi-Qiang&Zhou,%20Wei-Xing&Sornette,%20Didier&rft.genre=article&
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