Objective Bayesian analysis of JM model in software reliability

Yongqiang Lian, Yincai Tang and Yijun Wang

Computational Statistics & Data Analysis, 2017, vol. 109, issue C, 199-214

Abstract: Jelinski Moranda (JM) model is frequently used in software reliability. The objective Bayesian inference was proposed to estimate the parameters of JM model. Jeffreys prior and reference priors have been derived. Besides, the properties of corresponding posteriors were deduced and some modifications were made which made the posterior distributions proper. Then Gibbs sampling was utilized to obtain the Bayesian estimators, credible intervals and coverage probabilities of the parameters. Comparisons in the efficiency of the maximum likelihood estimators and Bayesian estimators under different priors for various sample sizes have been done by simulations and a real data set was analyzed for illustrative purpose.

Keywords: Software reliability; Objective Bayesian analysis; Jeffreys prior; Reference prior; Probability matching prior; Gibbs sampling (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:109:y:2017:i:c:p:199-214

DOI: 10.1016/j.csda.2016.12.006

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