ROBUST ESTIMATION OF THE HURST PARAMETER AND SELECTION OF AN ONSET SCALING

Cited 18 time in webofscience Cited 0 time in scopus
  • Hit : 27
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorPark, Juhyunko
dc.contributor.authorPark, Cheolwooko
dc.date.accessioned2021-06-11T01:50:38Z-
dc.date.available2021-06-11T01:50:38Z-
dc.date.created2021-06-11-
dc.date.created2021-06-11-
dc.date.issued2009-10-
dc.identifier.citationSTATISTICA SINICA, v.19, no.4, pp.1531 - 1555-
dc.identifier.issn1017-0405-
dc.identifier.urihttp://hdl.handle.net/10203/285783-
dc.description.abstractWe consider the problem of estimating the Hurst parameter for long-range dependent processes using wavelets. Wavelet techniques have been shown to effectively exploit the asymptotic linear relationship that forms the basis of constructing an estimator. However, it has been noticed that the commonly adopted standard wavelet estimator is vulnerable to various non-stationary phenomena that increasingly occur in practice, and thus leads to unreliable results. In this paper, we propose a new wavelet method for estimating the Hurst parameter that is robust to such non-stationarities as peaks, valleys, and trends. We point out that the new estimator arises as a simple alternative to the standard estimator and does not require an additional correction term that is subject to distributional assumptions. Additionally, we address the issue of selecting scales for the wavelet estimator, which is critical to properly exploiting the asymptotic relationship. We propose a new method based on standard regression diagnostic tools, which is easy to implement, and useful for providing informative goodness-of-fit measures. Several simulated examples are used for illustration and comparison. The proposed method is also applied to the estimation of the Hurst parameter of Internet traffic packet counts data.-
dc.languageEnglish-
dc.publisherSTATISTICA SINICA-
dc.titleROBUST ESTIMATION OF THE HURST PARAMETER AND SELECTION OF AN ONSET SCALING-
dc.typeArticle-
dc.identifier.wosid000271966500013-
dc.type.rimsART-
dc.citation.volume19-
dc.citation.issue4-
dc.citation.beginningpage1531-
dc.citation.endingpage1555-
dc.citation.publicationnameSTATISTICA SINICA-
dc.contributor.localauthorPark, Cheolwoo-
dc.contributor.nonIdAuthorPark, Juhyun-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorHurst parameter-
dc.subject.keywordAuthorlong-range dependence-
dc.subject.keywordAuthornon-stationarities-
dc.subject.keywordAuthorrobustness-
dc.subject.keywordAuthorwavelet spectrum-
dc.subject.keywordPlusSELF-SIMILARITY PARAMETER-
dc.subject.keywordPlusLONG-RANGE DEPENDENCE-
dc.subject.keywordPlusTIME-SERIES-
dc.subject.keywordPlusWAVELET-
dc.subject.keywordPlusINTERNET-
dc.subject.keywordPlusSIZER-
Appears in Collection
MA-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 18 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0