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The exponentiated Perks distribution

Author

Listed:
  • Bhupendra Singh

    (Ch. Charan Singh University)

  • Neha Choudhary

    (Ch. Charan Singh University)

Abstract

The study proposes the exponentiated Perks distribution as a generalization of Perks distribution. This generalized distribution provides monotone nondecreasing and bathtub shaped hazard rate function. We study its mathematical properties including mode, median, quantile function and order statistics. The estimation of the model parameters is discussed both in classical and Bayesian setups. The maximum likelihood estimates along with their standard errors and confidence intervals have been obtained. For Bayesian estimation, we use independent gamma priors for the model parameters. The posterior densities of the parameters are simulated using Metropolis–Hastings algorithm to obtain sample-based estimates and highest posterior density intervals. Applications of the proposed distribution to three real data sets have been demonstrated.

Suggested Citation

  • Bhupendra Singh & Neha Choudhary, 2017. "The exponentiated Perks 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. 8(2), pages 468-478, June.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-016-0451-1
    DOI: 10.1007/s13198-016-0451-1
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    References listed on IDEAS

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    1. Richards, S. J., 2008. "Applying Survival Models to Pensioner Mortality Data," British Actuarial Journal, Cambridge University Press, vol. 14(2), pages 257-303, July.
    2. Haberman, Steven & Renshaw, Arthur, 2011. "A comparative study of parametric mortality projection models," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 35-55, January.
    3. Ghitany, M.E. & Alqallaf, F. & Al-Mutairi, D.K. & Husain, H.A., 2011. "A two-parameter weighted Lindley distribution and its applications to survival data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(6), pages 1190-1201.
    4. Bhupendra Singh & K. Sharma & Shubhi Rathi & Gajraj Singh, 2012. "A generalized log-normal distribution and its goodness of fit to censored data," Computational Statistics, Springer, vol. 27(1), pages 51-67, March.
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