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Exponentiated Gull Alpha Exponential Distribution with Application to COVID‐19 Data

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  • Hazar A. Khogeer
  • Amani Alrumayh
  • M. M. Abd El-Raouf
  • Mutua Kilai
  • Ramy Aldallal

Abstract

In this paper, the main aim is to define a statistical distribution that can be used to model COVID‐19 data in Mexico and Canada. Using the method of exponentiation on the gull alpha exponential distribution introduces a new distribution with three parameters called the exponentiated gull alpha power exponential (EGAPE) distribution. The distribution has the benefit of being able to represent monotonic and nonmonotonic failure rates, both of which are often seen in dependability issues. It is possible to determine the quantile function as well as the skewness, kurtosis, and order statistics of the suggested distribution. The approach of maximum likelihood is used in order to calculate the parameters of the model, and the RMSE and average bias are utilised in order to evaluate how successful the strategy is. In conclusion, the flexibility of the new distribution is demonstrated by modeling COVID‐19 data. From the practical application, we can conclude that the proposed model outperformed the competing models and therefore can be used as a better option for modeling COVID‐19 and other related datasets.

Suggested Citation

  • Hazar A. Khogeer & Amani Alrumayh & M. M. Abd El-Raouf & Mutua Kilai & Ramy Aldallal, 2022. "Exponentiated Gull Alpha Exponential Distribution with Application to COVID‐19 Data," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:4255079
    DOI: 10.1155/2022/4255079
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    References listed on IDEAS

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    1. Deepesh Bhati & Mohd. Malik & H. Vaman, 2015. "Lindley–Exponential distribution: properties and applications," METRON, Springer;Sapienza Università di Roma, vol. 73(3), pages 335-357, December.
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