Multivariate reliability modelling with empirical Bayes inference

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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.
Original languageEnglish
Number of pages12
Publication statusUnpublished - 17 Jul 2007
EventISSAT international conference on modeling of complex systems and environments - Ho Chi Minh City, Vietnam
Duration: 16 Jul 200718 Jul 2007


ConferenceISSAT international conference on modeling of complex systems and environments
CityHo Chi Minh City, Vietnam


  • reliability growth model
  • empirical Bayes
  • engineering design process

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