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Objective Bayesian analysis of JM model in software reliability

Author

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  • Lian, Yongqiang
  • Tang, Yincai
  • Wang, Yijun

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.

Suggested Citation

  • Lian, Yongqiang & Tang, Yincai & Wang, Yijun, 2017. "Objective Bayesian analysis of JM model in software reliability," Computational Statistics & Data Analysis, Elsevier, vol. 109(C), pages 199-214.
    • Handle: RePEc:eee:csdana:v:109:y:2017:i:c:p:199-214
    DOI: 10.1016/j.csda.2016.12.006
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    References listed on IDEAS

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    1. B. Littlewood & J. L. Verrall, 1973. "A Bayesian Reliability Growth Model for Computer Software," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 22(3), pages 332-346, November.
    2. Herbert K. Weiss, 1956. "Estimation of Reliability Growth in a Complex System with a Poisson-Type Failure," Operations Research, INFORMS, vol. 4(5), pages 532-545, October.
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