A Bayesian Approach Using Nonhomogeneous Poisson Process for Software Reliability Models
نویسندگان
چکیده
Bayesian approach using nonhomogeneous Poisson process is considered for modeling software reliability problems. A generalized gamma and lognormal order statistics models are considered to model epochs of the failures of software. Metropolis algorithms along with Gibbs steps are proposed to perform the Bayesian inference of such models. Some Bayesian model diagnostics are developed and incorporated to verify further modeling assumptions. Model selection based on a pre-quential likelihood of conditional predictive ordinates is considered. The methodology developed in this paper is exempliied with a software reliability data set introduced by Jelinski and Moranda (1972).
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