Abstract
Collections of related Poisson or binomial counts arise, for example, from a number of different failures in similar machines or neighbouring time periods. A conventional Bayesian analysis requires a rather indirect prior specification and intensive numerical methods for posterior evaluations. An alternative approach using Bayes linear kinematics in which simple conjugate specifications for individual counts are linked through a Bayes linear belief structure is presented. Intensive numerical methods are not required. The use of transformations of the binomial and Poisson parameters is proposed. The approach is illustrated in two examples, one involving a Poisson count of failures, the other involving a binomial count in an analysis of failure times.
Original language | English |
---|---|
Pages (from-to) | 309-321 |
Number of pages | 13 |
Journal | Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability |
Volume | 224 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1 Dec 2010 |
Keywords
- linear kinematics
- bayesian analysis
- bayes linear methods
- count data
- failure times