In this paper, we introduce a Bayesian analysis for nonhomogeneous Poisson process in software reliability models assuming nonmonotonic intensity functions. Posterior summaries of interest are obtained using Markov chain Monte Carlo methods. We also present a Bayesian criterion to discriminate di er
Mixed poisson-type processes with application in software reliability
β Scribed by Y. Hayakawa; G. Telfar
- Book ID
- 104350781
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 445 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0895-7177
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β¦ Synopsis
we introduce one generalization of the mixed Poisson process referred to as the mixed Poisson-type process. An approach taken here is to assume the Ir-isotropy of interevent times and to define the parameter as a function of observable quantities. An inhomogeneous variant of the new process is studied as a software reliability model. As an illustration a numerical example is analyzed via the Gibbs sampler. The mixed Poisson-type process is constructed through probabilistic behaviour of observable quantities and includes the mixed Poisson process as the limiting case.
π SIMILAR VOLUMES
## Abstract Sequential tests for the product of Poisson parameters based on the generalized incomplete modified Bessel (g.i.m.B.) distributions are given. Applications to reliability and biometry are indicated.
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