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Alpha-Power Exponentiated Inverse Rayleigh distribution and its applications to real and simulated data

Author

Listed:
  • Muhammad Ali
  • Alamgir Khalil
  • Muhammad Ijaz
  • Noor Saeed

Abstract

The main goal of the current paper is to contribute to the existing literature of probability distributions. In this paper, a new probability distribution is generated by using the Alpha Power Family of distributions with the aim to model the data with non-monotonic failure rates and provides a better fit. The proposed distribution is called Alpha Power Exponentiated Inverse Rayleigh or in short APEIR distribution. Various statistical properties have been investigated including they are the order statistics, moments, residual life function, mean waiting time, quantiles, entropy, and stress-strength parameter. To estimate the parameters of the proposed distribution, the maximum likelihood method is employed. It has been proved theoretically that the proposed distribution provides a better fit to the data with monotonic as well as non-monotonic hazard rate shapes. Moreover, two real data sets are used to evaluate the significance and flexibility of the proposed distribution as compared to other probability distributions.

Suggested Citation

  • Muhammad Ali & Alamgir Khalil & Muhammad Ijaz & Noor Saeed, 2021. "Alpha-Power Exponentiated Inverse Rayleigh distribution and its applications to real and simulated data," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-17, January.
    • Handle: RePEc:plo:pone00:0245253
    DOI: 10.1371/journal.pone.0245253
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    References listed on IDEAS

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    1. Abbas Mahdavi & Debasis Kundu, 2017. "A new method for generating distributions with an application to exponential distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(13), pages 6543-6557, July.
    2. Ayman Alzaatreh & Carl Lee & Felix Famoye, 2013. "A new method for generating families of continuous distributions," METRON, Springer;Sapienza Università di Roma, vol. 71(1), pages 63-79, June.
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    Cited by:

    1. Sajid Hussain & Muhammad Sajid Rashid & Mahmood Ul Hassan & Rashid Ahmed, 2022. "The Generalized Alpha Exponent Power Family of Distributions: Properties and Applications," Mathematics, MDPI, vol. 10(9), pages 1-19, April.
    2. Hadeel S Klakattawi, 2022. "Survival analysis of cancer patients using a new extended Weibull distribution," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-20, February.
    3. Majdah Badr & Muhammad Ijaz, 2021. "The Exponentiated Exponential Burr XII distribution: Theory and application to lifetime and simulated data," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-20, March.

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