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A classical and Bayesian estimation of a k-components load-sharing parallel system

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  • Singh, Bhupendra
  • Sharma, K.K.
  • Kumar, Anuj

Abstract

The present study proposes the classical and Bayesian treatment to the estimation problem of parameters of a k-components load-sharing parallel system in which some of the components follow a constant failure-rate and the remaining follow a linearly increasing failure-rate. In the classical setup, the maximum likelihood estimates of the load-share parameters with their variances are obtained. (1-[gamma])100% individual, simultaneous, Bonferroni simultaneous and two bootstrap confidence intervals for the parameters have been constructed. Further, on recognizing the fact that life testing experiments are very time consuming, the parameters involved in the failure time distributions of the system are expected to follow some random variations. Therefore, Bayes estimates along with their posterior variances of the parameters are obtained by assuming gamma and Jeffrey's invariant priors. Markov Chain Monte Carlo techniques such as a Gibbs sampler have also been used to obtain the Bayes estimates and highest posterior density credible intervals when all the parameters follow gamma priors.

Suggested Citation

  • Singh, Bhupendra & Sharma, K.K. & Kumar, Anuj, 2008. "A classical and Bayesian estimation of a k-components load-sharing parallel system," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5175-5185, August.
  • Handle: RePEc:eee:csdana:v:52:y:2008:i:12:p:5175-5185
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    References listed on IDEAS

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    1. Paul H. Kvam & Edsel A. Pena, 2005. "Estimating Load-Sharing Properties in a Dynamic Reliability System," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 262-272, March.
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    Cited by:

    1. Pramendra Singh Pundir & Puneet Kumar Gupta, 2018. "Reliability Estimation in Load-Sharing System Model with Application to Real Data," Annals of Data Science, Springer, vol. 5(1), pages 69-91, March.
    2. Neha Choudhary & Abhishek Tyagi & Bhupendra Singh, 2022. "Analysing Load-Sharing System Model with Type-I and Type-II Failure Censored Data from Weibull Distribution," Annals of Data Science, Springer, vol. 9(4), pages 645-674, August.
    3. Azeem Ali & Sanku Dey & Haseeb Ur Rehman & Zeeshan Ali, 2019. "On Bayesian reliability estimation of a 1-out-of-k load sharing system model of modified Burr-III distribution," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(5), pages 1052-1081, October.
    4. Zhengcheng Zhang & Yonghong Yang & Danqing Li, 2022. "Estimation of parameters for load-sharing parallel systems under exponential Pareto distribution," Journal of Risk and Reliability, , vol. 236(2), pages 248-255, April.
    5. Brown, Bodunrin & Liu, Bin & McIntyre, Stuart & Revie, Matthew, 2022. "Reliability analysis of load-sharing systems with spatial dependence and proximity effects," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    6. Dewei Wang & Chendi Jiang & Chanseok Park, 2019. "Reliability analysis of load-sharing systems with memory," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 341-360, April.
    7. Singh, Bhupendra & Gupta, Puneet Kumar, 2012. "Load-sharing system model and its application to the real data set," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(9), pages 1615-1629.
    8. de Paula, Cassio Pereira & Visnadi, Lais Bittencourt & de Castro, Helio Fiori, 2019. "Multi-objective optimization in redundant system considering load sharing," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 17-27.
    9. Levitin, Gregory & Xing, Liudong & Ben-Haim, Hanoch & Dai, Yuanshun, 2016. "Optimal task partition and state-dependent loading in heterogeneous two-element work sharing system," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 97-108.
    10. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2018. "Optimal work distribution and backup frequency for two non-identical work sharing elements," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 127-136.

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