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Fuzzy Reliability Analysis of the COVID‐19 Mortality Rate Using a New Modified Kies Kumaraswamy Model

Author

Listed:
  • Fathy H. Riad
  • Bader Alruwaili
  • Ehab M. Almetwally
  • Eslam Hussam

Abstract

In this paper, we developed a novel superior distribution, demonstrated and derived its mathematical features, and assessed its fuzzy reliability function. The novel distribution has numerous advantages, including the fact that its CDf and PDf have a closed shape, making it particularly relevant in many domains of data science. We used both conventional and Bayesian approaches to make various sorts of estimations. A simulation research was carried out to investigate the performance of the classical and Bayesian estimators. Finally, we fitted a COVID‐19 mortality real data set to the suggested distribution in order to compare its efficiency to that of its rivals.

Suggested Citation

  • Fathy H. Riad & Bader Alruwaili & Ehab M. Almetwally & Eslam Hussam, 2022. "Fuzzy Reliability Analysis of the COVID‐19 Mortality Rate Using a New Modified Kies Kumaraswamy Model," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:3427521
    DOI: 10.1155/2022/3427521
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    References listed on IDEAS

    as
    1. Abdulhakim A. Al-Babtain & Mohammed K. Shakhatreh & Mazen Nassar & Ahmed Z. Afify, 2020. "A New Modified Kies Family: Properties, Estimation Under Complete and Type-II Censored Samples, and Engineering Applications," Mathematics, MDPI, vol. 8(8), pages 1-24, August.
    2. Lalmuanawma, Samuel & Hussain, Jamal & Chhakchhuak, Lalrinfela, 2020. "Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
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