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A New Goodness-of-Fit Test for the Logistic Distribution

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  • Hadi Alizadeh Noughabi

    (University of Birjand)

Abstract

The logistic distribution has been widely used to model growth curves in survival analysis and biological studies. In this article, we propose a goodness of fit test for the logistic distribution based on a new estimate of Kullback-Leibler information. The properties of the test statistic are presented. In order to compute the proposed test statistic, parameters of the logistic distribution are estimated by approximate maximum likelihood estimators (AMLEs) suggested by Balakrishnan and Cohen (1990), which are simple explicit estimators. Through a simulation study, power values of the proposed test are compared with some prominent existing tests. Finally, an illustrative example is presented and analyzed.

Suggested Citation

  • Hadi Alizadeh Noughabi, 2022. "A New Goodness-of-Fit Test for the Logistic Distribution," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 303-319, May.
    • Handle: RePEc:spr:sankhb:v:84:y:2022:i:1:d:10.1007_s13571-021-00262-1
    DOI: 10.1007/s13571-021-00262-1
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    References listed on IDEAS

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    1. Hadi Alizadeh Noughabi, 2015. "Empirical likelihood ratio-based goodness-of-fit test for the logistic distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(9), pages 1973-1983, September.
    2. Hadi Alizadeh Noughabi, 2017. "Gini index based goodness-of-fit test for the logistic distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(14), pages 7114-7124, July.
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