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Statistical inference for the generalized inverted exponential distribution based on upper record values

Author

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  • Dey, Sanku
  • Dey, Tanujit
  • Luckett, Daniel J.

Abstract

In this paper, non-Bayesian and Bayesian estimators for the unknown parameters are obtained based on records from the generalized inverted exponential distribution. Bayes’ estimators of the unknown parameters are obtained under symmetric and asymmetric loss functions using gamma priors on both the shape and the scale parameters. The Bayes estimators cannot be obtained in explicit forms. So we propose Markov Chain Monte Carlo (MCMC) techniques to generate samples from the posterior distributions and in turn computing the Bayes estimators. We have also derived the Bayes interval of this distribution and discussed both frequentist and the Bayesian prediction intervals of the future record values based on the observed record values. Monte Carlo simulations are performed to compare the performances of the proposed methods, and a data set has been analyzed for illustrative purposes.

Suggested Citation

  • Dey, Sanku & Dey, Tanujit & Luckett, Daniel J., 2016. "Statistical inference for the generalized inverted exponential distribution based on upper record values," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 120(C), pages 64-78.
    • Handle: RePEc:eee:matcom:v:120:y:2016:i:c:p:64-78
    DOI: 10.1016/j.matcom.2015.06.012
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    References listed on IDEAS

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    1. Sanku Dey & Tanujit Dey, 2014. "On progressively censored generalized inverted exponential distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(12), pages 2557-2576, December.
    2. Jafar Ahmadi & M. Doostparast, 2006. "Bayesian estimation and prediction for some life distributions based on record values," Statistical Papers, Springer, vol. 47(3), pages 373-392, June.
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    Cited by:

    1. Liang Wang & Huizhong Lin & Yuhlong Lio & Yogesh Mani Tripathi, 2022. "Interval Estimation of Generalized Inverted Exponential Distribution under Records Data: A Comparison Perspective," Mathematics, MDPI, vol. 10(7), pages 1-20, March.
    2. Mahmoud R. Mahmoud & Hiba Z. Muhammed & Ahmed R. El-Saeed, 2023. "Inference for Generalized Inverted Exponential Distribution Under Progressive Type-I Censoring Scheme in Presence of Competing Risks Model," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 43-76, February.
    3. Wang, Liang & Wu, Shuo-Jye & Zhang, Chunfang & Dey, Sanku & Tripathi, Yogesh Mani, 2022. "Analysis for constant-stress model on multicomponent system from generalized inverted exponential distribution with stress dependent parameters," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 301-316.
    4. Sukhdev Singh & Yogesh Mani Tripathi & Shuo-Jye Wu, 2017. "Bayesian estimation and prediction based on lognormal record values," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(5), pages 916-940, April.
    5. Kousik Maiti & Suchandan Kayal, 2023. "Estimating Reliability Characteristics of the Log-Logistic Distribution Under Progressive Censoring with Two Applications," Annals of Data Science, Springer, vol. 10(1), pages 89-128, February.

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