A Bayesian analysis of industrial lifetime data with Weibull distributions - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Reports (Research Report) Year : 2006

A Bayesian analysis of industrial lifetime data with Weibull distributions

Nicolas Bousquet

Abstract

The context of our study is industrial reliability, where lifetime data are usually censored and in small number. Background information is available from experts. Our prior subjective knowledge is only about the lifetime of an industrial component and not about the parameters of a Weibull distribution which represents this lifetime. We propose to focus the discussion between the experts and the industrial analyst about the size of {\it virtual} data representing the variability of the expert opinion. Indeed, this size is one of the scarce indicators that both can understand. The prior calibration is made easy, and some methods and indicators including a default calibration method are proposed to help the Bayesian analyst (they can be extended to inferences on other distributions than Weibull). Besides, the posterior computation by importance sampling is simple and satisfying. Finally, through a real example, the flexibility of the elicitation is illustrated.
Fichier principal
Vignette du fichier
RR-6025.pdf (388.51 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

inria-00115528 , version 1 (21-11-2006)
inria-00115528 , version 2 (22-11-2006)
inria-00115528 , version 3 (22-11-2006)
inria-00115528 , version 4 (23-11-2006)

Identifiers

  • HAL Id : inria-00115528 , version 4

Cite

Nicolas Bousquet. A Bayesian analysis of industrial lifetime data with Weibull distributions. [Research Report] RR-6025, INRIA. 2006, pp.24. ⟨inria-00115528v4⟩
155 View
1049 Download

Share

Gmail Facebook Twitter LinkedIn More