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Statistical inference based on Lindley record data

Author

Listed:
  • A. Asgharzadeh

    (Faculty of Mathematical Sciences University of Mazandaran)

  • A. Fallah

    (Payame Noor University)

  • M. Z. Raqab

    (Kuwait University
    The University of Jordan)

  • R. Valiollahi

    (Semnan University)

Abstract

Based on record statistics from Lindley distribution, we consider here the problem of estimating the model parameter and predicting the unobserved records. Frequentist and Bayesian analyses are discussed for making some inferences for the model parameter and prediction of unobserved records. Frequentist methods involving maximum likelihood estimation and moments based estimation and Bayesian sampling-based technique are applied for estimating the unknown shape parameter as well as predicting the future unobserved units. The corresponding point predictors and credible intervals of future record values based on an informative set of records can be developed. Real data analysis has been performed for illustrative purposes.

Suggested Citation

  • A. Asgharzadeh & A. Fallah & M. Z. Raqab & R. Valiollahi, 2018. "Statistical inference based on Lindley record data," Statistical Papers, Springer, vol. 59(2), pages 759-779, June.
    • Handle: RePEc:spr:stpapr:v:59:y:2018:i:2:d:10.1007_s00362-016-0788-1
    DOI: 10.1007/s00362-016-0788-1
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    References listed on IDEAS

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    8. Krishna, Hare & Kumar, Kapil, 2011. "Reliability estimation in Lindley distribution with progressively type II right censored sample," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(2), pages 281-294.
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    Cited by:

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    2. A. Asgharzadeh & S. F. Bagheri & N. A. Ibrahim & M. R. Abubakar, 2020. "Optimal confidence regions for the two-parameter exponential distribution based on records," Computational Statistics, Springer, vol. 35(1), pages 309-326, March.

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