Effects of trends and seasonalities on robustness of the Hurst parameter estimators

dc.contributor.authorYe, Xianming
dc.contributor.authorXia, Xiaohua
dc.contributor.authorZhang, Jiangfeng
dc.contributor.authorChen, Yangquan
dc.contributor.emailxianming.ye@up.ac.zaen_US
dc.date.accessioned2013-10-03T12:25:02Z
dc.date.available2013-10-03T12:25:02Z
dc.date.issued2013
dc.description.abstractLong-range dependence (LRD) is discovered in time series arising from different fields, especially in network traffic and econometrics. Detecting the presence and the intensity of LRD plays a crucial role in time-series analysis and fractional system identification. The existence of LRD is usually indicated by the Hurst parameters. Up to now, many Hurst parameter estimators have been proposed in order to identify the LRD property involved in a time series. Since different estimators have different accuracy and robustness performances, in this study, 13 most popular Hurst parameter estimators are summarised and their estimation performances are investigated. LRD processes with known Hurst parameters are generated as the control data set for the robustness evaluation. In addition, three types of LRD processes are also obtained as the test signals by adding noises in terms of means, trends and seasonalities to the control data set. All 13 Hurst parameter estimators are applied to these LRD processes to estimate the existing Hurst parameters. The estimation results are documented and quantified by the standard errors. Conclusions of the accuracy and robustness performances of the estimators are drawn by comparing the estimation results.en_US
dc.description.librarianhb2013en_US
dc.description.sponsorshipThe National Hub for the Postgraduate Programme in Energy Efficiency and Demand Side Management at the University of Pretoria.en_US
dc.description.urihttp://www.ietdl.orgen_US
dc.identifier.citationYe, X, Xia, X, Zhang, J & Chen, Y 2013, 'Effects of trends and seasonalities on robustness of the Hurst parameter estimators', IET Signal Processing, vol. 6, no. 9, pp. 849-856.en_US
dc.identifier.issn1751-9675(print)
dc.identifier.issn1751-9683 (online)
dc.identifier.other10.1049/iet-spr.2012.0050
dc.identifier.urihttp://hdl.handle.net/2263/31900
dc.language.isoenen_US
dc.publisherInstitution of Engineering and Technologyen_US
dc.rightsInstitution of Engineering and Technology. This paper is a postprint of a paper submitted to and accepted for publication inIET Signal Processing and is subject to Institution of Engineering. This paper is a postprint of a paper submitted to and accepted for publication in IET Signal Processing and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.en_US
dc.subjectHurst parametersen_US
dc.subjectfGnen_US
dc.subjectRobustnessen_US
dc.subjectLong-range dependence (LRD)en_US
dc.titleEffects of trends and seasonalities on robustness of the Hurst parameter estimatorsen_US
dc.typePostprint Articleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Ye_Effects(2013).pdf
Size:
309.95 KB
Format:
Adobe Portable Document Format
Description:
Postprint Article

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: