Abstract

A fundamental logical problem in the Bayesian inference of a series system's failure probability is described, a practical means for its mitigation is discussed, and its application to space launch vehicles is illustrated. The problem is the ldquoBayesian Anomaly,rdquo the difference in the system's failure probability per operation inferred from prior estimates, and test or operational experience applied at a lower-level of the system; and from the convolution of the same priors, and of the same experience applied at the system level (or any level above the first). In particular, unlike in a classical inference, the mean estimates differ critically. Although it is not possible to entirely resolve the problem, a practical procedure for mitigating it, establishing consistency among the mean and variance estimates at the two levels, is delineated.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.