Bayesian Inference and Model Selection for Software Growth Reliability Models using Gibbs Sampler

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Journal of Korean Society for Quality Management > Volume 27(3); 1999 > Article

Journal of Korean Society for Quality Management 1999;27(3): 125-.

몬테칼로 깁스방법을 적용한 소프트웨어 신뢰도 성장모형에 대한 베이지안 추론과 모형선택에 관한 연구

김희철¹, 이승주²

¹동국대학교 통계학과
²청주대학교 응용통계학과

Bayesian Inference and Model Selection for Software Growth Reliability Models using Gibbs Sampler

ABSTRACT

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, we could avoid the multiple integration by the use of Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference and model selection method for Jelinski-Moranda and Goel-Okumoto and Schick-Wolverton models in software reliability with Poisson prior information are studied. For model selection, we explored the relative error.