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Article: Detecting change points in the stress-strength reliability P(X < Y)

TitleDetecting change points in the stress-strength reliability P(X < Y)
Authors
KeywordsDynamic programming
Multiple change-points detection
Stress-strength model
Issue Date2019
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/1524-1904/
Citation
Applied Stochastic Models in Business and Industry, 2019, v. 35 n. 3, p. 837-857 How to Cite?
AbstractWe address the statistical problem of detecting change points in the stress‐strength reliability R=P(X < Y) in a sequence of paired variables (X,Y). Without specifying their underlying distributions, we embed this nonparametric problem into a parametric framework and apply the maximum likelihood method via a dynamic programming approach to determine the locations of the change points in R. Under some mild conditions, we show the consistency and asymptotic properties of the procedure to locate the change points. Simulation experiments reveal that, in comparison with existing parametric and nonparametric change‐point detection methods, our proposed method performs well in detecting both single and multiple change points in R in terms of the accuracy of the location estimation and the computation time. Applications to real data demonstrate the usefulness of our proposed methodology for detecting the change points in the stress‐strength reliability R. Supplementary materials are available online.
Persistent Identifierhttp://hdl.handle.net/10722/275755
ISSN
2021 Impact Factor: 1.497
2020 SCImago Journal Rankings: 0.413
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, H-
dc.contributor.authorYu, PLH-
dc.contributor.authorAlvo, M-
dc.date.accessioned2019-09-10T02:49:02Z-
dc.date.available2019-09-10T02:49:02Z-
dc.date.issued2019-
dc.identifier.citationApplied Stochastic Models in Business and Industry, 2019, v. 35 n. 3, p. 837-857-
dc.identifier.issn1524-1904-
dc.identifier.urihttp://hdl.handle.net/10722/275755-
dc.description.abstractWe address the statistical problem of detecting change points in the stress‐strength reliability R=P(X < Y) in a sequence of paired variables (X,Y). Without specifying their underlying distributions, we embed this nonparametric problem into a parametric framework and apply the maximum likelihood method via a dynamic programming approach to determine the locations of the change points in R. Under some mild conditions, we show the consistency and asymptotic properties of the procedure to locate the change points. Simulation experiments reveal that, in comparison with existing parametric and nonparametric change‐point detection methods, our proposed method performs well in detecting both single and multiple change points in R in terms of the accuracy of the location estimation and the computation time. Applications to real data demonstrate the usefulness of our proposed methodology for detecting the change points in the stress‐strength reliability R. Supplementary materials are available online.-
dc.languageeng-
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/1524-1904/-
dc.relation.ispartofApplied Stochastic Models in Business and Industry-
dc.subjectDynamic programming-
dc.subjectMultiple change-points detection-
dc.subjectStress-strength model-
dc.titleDetecting change points in the stress-strength reliability P(X < Y)-
dc.typeArticle-
dc.identifier.emailYu, PLH: plhyu@hku.hk-
dc.identifier.authorityYu, PLH=rp00835-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/asmb.2413-
dc.identifier.scopuseid_2-s2.0-85055735484-
dc.identifier.hkuros303898-
dc.identifier.volume35-
dc.identifier.issue3-
dc.identifier.spage837-
dc.identifier.epage857-
dc.identifier.isiWOS:000471712700028-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl1524-1904-

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