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Estimation Of Stress-Strength Reliability For The Pareto Distribution Based On Upper Record Values

Author

Listed:
  • Rahmath Manzil Juvairiyya

    (Department of Statistics, Farook College)

  • Parameshwaranpillai Anilkumar

    (Department of Statistics, Farook College)

Abstract

In this paper, the estimation of stress-strength reliability based on upper record values is considered when X and Y are independent random variables having a Pareto distribution with the same scale parameter and with different shape parameters. The maximum likelihood estimator (MLE), the approximate Bayes estimators and the exact confidence interval of the stress-strength reliability are obtained. A Monte Carlo simulation study is conducted to investigate the merits of the proposed methods. A real data analysis is presented for illustrative purpose.

Suggested Citation

  • Rahmath Manzil Juvairiyya & Parameshwaranpillai Anilkumar, 2018. "Estimation Of Stress-Strength Reliability For The Pareto Distribution Based On Upper Record Values," Statistica, Department of Statistics, University of Bologna, vol. 78(4), pages 397-409.
    • Handle: RePEc:bot:rivsta:v:78:y:2018:i:4:p:397-409
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    Cited by:

    1. Yasuyuki Hamura & Tatsuya Kubokawa, 2022. "Bayesian predictive density estimation with parametric constraints for the exponential distribution with unknown location," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(4), pages 515-536, May.

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