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A Bayesian Approach to Parallel Stress-Strength Models

Author

Listed:
  • Durán Mónica
  • Peña Alexis
  • Salinas Víctor H.

    (Departamento de Matemática y Ciencia de la Computación, Universidad de Santiago de Chile, Casilla 307-Correo 2, Santiago-Chile.)

Abstract

This work presents a Bayesian approach for estimating the reliability of a parallel multi-component system. It is assumed that the strengths of the components are independent random variables, which are subjected to a common stress with the same distribution. It is supposed that the failure times follow exponential and Weibull distributions, respectively. The Bayesian analysis is developed assuming a highly informative prior and a less informative prior distribution, respectively. A simulation based on certain data sets is used to study the performance of the Bayesian solutions. The solutions are computed by Markov Chain Monte Carlo (MCMC) methods. Finally, some observations are made in relation to the maximum likelihood method and some extensions are discussed.

Suggested Citation

  • Durán Mónica & Peña Alexis & Salinas Víctor H., 2007. "A Bayesian Approach to Parallel Stress-Strength Models," Stochastics and Quality Control, De Gruyter, vol. 22(1), pages 71-85, January.
    • Handle: RePEc:bpj:ecqcon:v:22:y:2007:i:1:p:71-85:n:9
    DOI: 10.1515/EQC.2007.71
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