Reliability prediction through degradation data modeling using a quasi-likelihood approach
Proceedings - Annual Reliability and Maintainability Symposium
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2014
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sg-nus-scholar.10635-723942015-01-12T22:26:03Z Reliability prediction through degradation data modeling using a quasi-likelihood approach Jayaram, J.S.R. Girish, T. INDUSTRIAL & SYSTEMS ENGINEERING Degradation data Generalized Estimating Equations Reliability Proceedings - Annual Reliability and Maintainability Symposium 193-199 2014-06-19T04:54:25Z 2014-06-19T04:54:25Z 2005 Conference Paper Jayaram, J.S.R.,Girish, T. (2005). Reliability prediction through degradation data modeling using a quasi-likelihood approach. Proceedings - Annual Reliability and Maintainability Symposium : 193-199. ScholarBank@NUS Repository. 0149144X http://scholarbank.nus.edu.sg/handle/10635/72394 NOT_IN_WOS Scopus |
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Degradation data Generalized Estimating Equations Reliability |
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Degradation data Generalized Estimating Equations Reliability Jayaram, J.S.R. Girish, T. Reliability prediction through degradation data modeling using a quasi-likelihood approach |
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Proceedings - Annual Reliability and Maintainability Symposium |
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INDUSTRIAL & SYSTEMS ENGINEERING |
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INDUSTRIAL & SYSTEMS ENGINEERING Jayaram, J.S.R. Girish, T. |
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Conference or Workshop Item |
author |
Jayaram, J.S.R. Girish, T. |
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Jayaram, J.S.R. |
title |
Reliability prediction through degradation data modeling using a quasi-likelihood approach |
title_short |
Reliability prediction through degradation data modeling using a quasi-likelihood approach |
title_full |
Reliability prediction through degradation data modeling using a quasi-likelihood approach |
title_fullStr |
Reliability prediction through degradation data modeling using a quasi-likelihood approach |
title_full_unstemmed |
Reliability prediction through degradation data modeling using a quasi-likelihood approach |
title_sort |
reliability prediction through degradation data modeling using a quasi-likelihood approach |
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2014 |
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http://scholarbank.nus.edu.sg/handle/10635/72394 |
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1681087557912231936 |