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Goodness of Fit Tests for the Log-Logistic Distribution Based on Cumulative Entropy under Progressive Type II Censoring

Author

Listed:
  • Yuge Du

    (Department of Mathematics, Beijing Jiaotong University, Beijing 100044, China)

  • Wenhao Gui

    (Department of Mathematics, Beijing Jiaotong University, Beijing 100044, China)

Abstract

In this paper, we propose two new methods to perform goodness-of-fit tests on the log-logistic distribution under progressive Type II censoring based on the cumulative residual Kullback-Leibler information and cumulative Kullback-Leibler information. Maximum likelihood estimation and the EM algorithm are used for statistical inference of the unknown parameter. The Monte Carlo simulation is conducted to study the power analysis on the alternative distributions of the hazard function monotonically increasing and decreasing. Finally, we present illustrative examples to show the applicability of the proposed methods.

Suggested Citation

  • Yuge Du & Wenhao Gui, 2019. "Goodness of Fit Tests for the Log-Logistic Distribution Based on Cumulative Entropy under Progressive Type II Censoring," Mathematics, MDPI, vol. 7(4), pages 1-20, April.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:4:p:361-:d:224666
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    References listed on IDEAS

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    1. Daniele Cristina Tita Granzotto & Francisco Louzada, 2015. "The Transmuted Log-Logistic Distribution: Modeling, Inference, and an Application to a Polled Tabapua Race Time up to First Calving Data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(16), pages 3387-3402, August.
    2. R. R. L. Kantam & G. Srinivasa Rao & B. Sriram, 2006. "An economic reliability test plan: Log-logistic distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(3), pages 291-296.
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    Cited by:

    1. Abdullah Fathi & Al-Wageh A. Farghal & Ahmed A. Soliman, 2022. "Bayesian and Non-Bayesian Inference for Weibull Inverted Exponential Model under Progressive First-Failure Censoring Data," Mathematics, MDPI, vol. 10(10), pages 1-19, May.

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