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 (Unpublished)

[thumbnail of QuigleyWallsISSAT2007-multivariate-reliability-modelling]
Preview
PDF. Filename: Quigley_and_Walls_Multivaiate_Reliability.pdf
Preprint

Download (331kB)| Preview

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.