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Exponentiated Generalized Inverse Flexible Weibull Distribution: Bayesian and Non-Bayesian Estimation Under Complete and Type II Censored Samples with Applications

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Abstract

In this paper, a new 4-parameter exponentiated generalized inverse flexible Weibull distribution is proposed. Some of its statistical properties are studied. The aim of this paper is to estimate the model parameters via several approaches, namely, maximum likelihood, maximum product spacing and Bayesian. According to Bayesian approach, several techniques are used to get the Bayesian estimators, namely, standard error function, Linex loss function and entropy loss function. The estimation herein is based on complete and censored samples. Markov Chain Monte Carlo simulation is used to discuss the behavior of the estimators for each approach. Finally, two real data sets are analyzed to obtain the flexibility of the proposed model.

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Authors and Affiliations

  1. Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia

    M. El-Morshedy

  2. Department of Mathematics, Faculty of Science, Mansoura University, Mansoura, 35516, Egypt

    M. El-Morshedy, M. S. Eliwa, A. El-Gohary & R. EL-Desokey

  3. Faculty of Business Administration, Delta University of Science and Technology, Mansoura, Egypt

    Ehab M. Almetwally

  4. Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, 12613, Egypt

    Ehab M. Almetwally

Authors
  1. M. El-Morshedy
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  2. M. S. Eliwa
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  3. A. El-Gohary
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  4. Ehab M. Almetwally
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  5. R. EL-Desokey
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Correspondence to M. El-Morshedy.

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El-Morshedy, M., Eliwa, M.S., El-Gohary, A. et al. Exponentiated Generalized Inverse Flexible Weibull Distribution: Bayesian and Non-Bayesian Estimation Under Complete and Type II Censored Samples with Applications. Commun. Math. Stat. 10, 413–434 (2022). https://doi.org/10.1007/s40304-020-00225-4

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  • DOI: https://doi.org/10.1007/s40304-020-00225-4

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