Multivariate reliability modelling with empirical Bayes inference
Quigley, J.L. and Walls, L.A. (2007) Multivariate reliability modelling with empirical Bayes inference. In: ISSAT international conference on modeling of complex systems and environments, 2007-07-16 - 2007-07-18. (Unpublished)
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Abstract
Recent developments in technology permit detailed descriptions of system performance to be collected and stored. Consequently, more data are available about the occurrence, or non-occurrence, of events across a range of classes through time. Typically this implies that reliability analysis has more information about the exposure history of a system within different classes of events. For highly reliable systems, there may be relatively few failure events. Thus there is a need to develop statistical inference to support reliability estimation when there is a low ratio of failures relative to event classes. In this paper we show how Empirical Bayes methods can be used to estimate a multivariate reliability function for a system by modelling the vector of times to realise each failure root cause.
ORCID iDs
Quigley, J.L. ORCID: https://orcid.org/0000-0002-7253-8470 and Walls, L.A. ORCID: https://orcid.org/0000-0001-7016-9141;-
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Item type: Conference or Workshop Item(Paper) ID code: 18157 Dates: DateEvent17 July 2007PublishedSubjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management Department: Strathclyde Business School > Management Science Depositing user: Strathprints Administrator Date deposited: 11 May 2010 13:56 Last modified: 11 Nov 2024 16:25 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/18157