Please use this identifier to cite or link to this item: https://doi.org/10.1109/TR.2008.916867
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dc.titleAn application of the EM algorithm to degradation modeling
dc.contributor.authorNg, T.S.
dc.date.accessioned2014-06-17T06:59:00Z
dc.date.available2014-06-17T06:59:00Z
dc.date.issued2008-03
dc.identifier.citationNg, T.S. (2008-03). An application of the EM algorithm to degradation modeling. IEEE Transactions on Reliability 57 (1) : 2-13. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/TR.2008.916867" target="_blank">https://doi.org/10.1109/TR.2008.916867</a>
dc.identifier.issn00189529
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/62998
dc.description.abstractWe consider a class of degradation processes that can consist of distinct phases of behavior. In particular, the degradation rates could possibly increase or decrease in a non-smooth manner at some point in time when the underlying degradation process changes phase. To model the degradation path of a given device, we use an independent-increments stochastic process with a single unobserved change-point. Furthermore, we assume that the change-point varies randomly from device-to-device. The likelihood functions for such a model are analytically intractable, so in this paper we develop an EM algorithm for this model to obtain the maximum likelihood estimators efficiently. We demonstrate the applicability of the method using two different models, and present some computational results of our implementation. © 2008 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TR.2008.916867
dc.sourceScopus
dc.subjectChange-points
dc.subjectDegradation modeling
dc.subjectEM algorithm
dc.subjectMaximum likelihood estimation
dc.typeArticle
dc.contributor.departmentINDUSTRIAL & SYSTEMS ENGINEERING
dc.description.doi10.1109/TR.2008.916867
dc.description.sourcetitleIEEE Transactions on Reliability
dc.description.volume57
dc.description.issue1
dc.description.page2-13
dc.description.codenIEERA
dc.identifier.isiutNOT_IN_WOS
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