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Empirical likelihood ratio-based goodness-of-fit test for the logistic distribution

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  • Hadi Alizadeh Noughabi

Abstract

The logistic distribution has been 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 the empirical likelihood ratio. The test is constructed based on the methodology introduced by Vexler and Gurevich [17]. In order to compute the test statistic, parameters of the distribution are estimated by the method of maximum likelihood. Power comparisons of the proposed test with some known competing tests are carried out via simulations. Finally, an illustrative example is presented and analyzed.

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  • 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.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:9:p:1973-1983
    DOI: 10.1080/02664763.2015.1014893
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    1. Albert Vexler & Young Min Kim & Jihnhee Yu & Nicole A. Lazar & Alan D. Hutson, 2014. "Computing Critical Values of Exact Tests by Incorporating Monte Carlo Simulations Combined with Statistical Tables," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1013-1030, December.
    2. Albert Vexler & Jihnhee Yu & Alan D. Hutson, 2011. "Likelihood testing populations modeled by autoregressive process subject to the limit of detection in applications to longitudinal biomedical data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(7), pages 1333-1346, May.
    3. Vexler, Albert & Gurevich, Gregory, 2010. "Empirical likelihood ratios applied to goodness-of-fit tests based on sample entropy," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 531-545, February.
    4. Modarres, Reza & Nayak, Tapan K. & Gastwirth, Joseph L., 2002. "Estimation of upper quantiles under model and parameter uncertainty," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 529-554, June.
    5. Albert Vexler & Shuling Liu & Enrique F. Schisterman, 2011. "Nonparametric-likelihood inference based on cost-effectively-sampled-data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 769-783, February.
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    Cited by:

    1. 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.
    2. Gerrit Lodewicus Grobler & Elzanie Bothma & James Samuel Allison, 2022. "Testing for the Rayleigh Distribution: A New Test with Comparisons to Tests for Exponentiality Based on Transformed Data," Mathematics, MDPI, vol. 10(8), pages 1-17, April.

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