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A New Extension of the Topp–Leone-Family of Models with Applications to Real Data

Author

Listed:
  • Mustapha Muhammad

    (Guangdong University of Petrochemical Technology)

  • Lixia Liu

    (Hebei Normal University)

  • Badamasi Abba

    (Central South University
    Yusuf Maitama Sule University)

  • Isyaku Muhammad

    (University of Electronic Science and Technology of China)

  • Mouna Bouchane

    (Hebei Normal University)

  • Hexin Zhang

    (Hebei Normal University)

  • Sani Musa

    (Sule Lamido University)

Abstract

In this article, we proposed a new extension of the Topp–Leone family of distributions. Some important properties of the model are developed, such as quantile function, stochastic ordering, model series representation, moments, stress–strength reliability parameter, Renyi entropy, order statistics, and moment of residual life. A particular member called new extended Topp–Leone exponential (NETLE) is discussed. Maximum likelihood estimation (MLE), least-square estimation (LSE), and percentile estimation (PE) are used for the model parameter estimation. Simulation studies were conducted using NETLE to assess the MLE, LSE, and PE performance by examining their bias and mean square error (MSE), and the result was satisfactory. Finally, the applications of the NETLE to two real data sets are provided to illustrate the importance of the NETLG families in practice; the data sets consist of daily new deaths due to COVID-19 in California and New Jersey, USA. The new model outperformed many other existing Topp–Leone’s and exponential related distributions based on the real data illustrations.

Suggested Citation

  • Mustapha Muhammad & Lixia Liu & Badamasi Abba & Isyaku Muhammad & Mouna Bouchane & Hexin Zhang & Sani Musa, 2023. "A New Extension of the Topp–Leone-Family of Models with Applications to Real Data," Annals of Data Science, Springer, vol. 10(1), pages 225-250, February.
    • Handle: RePEc:spr:aodasc:v:10:y:2023:i:1:d:10.1007_s40745-022-00456-y
    DOI: 10.1007/s40745-022-00456-y
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    References listed on IDEAS

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    1. Mustapha Muhammad & Rashad A. R. Bantan & Lixia Liu & Christophe Chesneau & Muhammad H. Tahir & Farrukh Jamal & Mohammed Elgarhy, 2021. "A New Extended Cosine—G Distributions for Lifetime Studies," Mathematics, MDPI, vol. 9(21), pages 1-29, October.
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    5. Anurag Pathak & Manoj Kumar & Sanjay Kumar Singh & Umesh Singh, 2022. "Statistical Inferences: Based on Exponentiated Exponential Model to Assess Novel Corona Virus (COVID-19) Kerala Patient Data," Annals of Data Science, Springer, vol. 9(1), pages 101-119, February.
    6. Muhammad Ahsan-ul-Haq & Mukhtar Ahmed & Javeria Zafar & Pedro Luiz Ramos, 2022. "Modeling of COVID-19 Cases in Pakistan Using Lifetime Probability Distributions," Annals of Data Science, Springer, vol. 9(1), pages 141-152, February.
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    Cited by:

    1. Maria T. Vasileva, 2023. "On Topp-Leone-G Power Series: Saturation in the Hausdorff Sense and Applications," Mathematics, MDPI, vol. 11(22), pages 1-11, November.

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