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A jackknife empirical likelihood ratio test for log-symmetric distributions

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  • Avhad, Ganesh Vishnu
  • Lahiri, Ananya

Abstract

A nonparametric test for assessing log-symmetric distributions is proposed, including the jackknife empirical likelihood and adjusted jackknife empirical likelihood ratio tests. The asymptotic distribution of the test statistic has been derived as well. A comprehensive Monte Carlo simulation study shows that the proposed tests exhibit good power against various alternative distributions. Additionally, the method is demonstrated using two real data sets to highlight their practical applicability.

Suggested Citation

  • Avhad, Ganesh Vishnu & Lahiri, Ananya, 2025. "A jackknife empirical likelihood ratio test for log-symmetric distributions," Statistics & Probability Letters, Elsevier, vol. 222(C).
    • Handle: RePEc:eee:stapro:v:222:y:2025:i:c:s0167715225000392
    DOI: 10.1016/j.spl.2025.110394
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    References listed on IDEAS

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    1. Jing, Bing-Yi & Yuan, Junqing & Zhou, Wang, 2009. "Jackknife Empirical Likelihood," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1224-1232.
    2. Bookstaber, Richard M & McDonald, James B, 1987. "A General Distribution for Describing Security Price Returns," The Journal of Business, University of Chicago Press, vol. 60(3), pages 401-424, July.
    3. Ivanović, Blagoje & Milošević, Bojana & Obradović, Marko, 2020. "Comparison of symmetry tests against some skew-symmetric alternatives in i.i.d. and non-i.i.d. setting," Computational Statistics & Data Analysis, Elsevier, vol. 151(C).
    4. Zhao, Yichuan & Meng, Xueping & Yang, Hanfang, 2015. "Jackknife empirical likelihood inference for the mean absolute deviation," Computational Statistics & Data Analysis, Elsevier, vol. 91(C), pages 92-101.
    5. Milošević, B. & Obradović, M., 2016. "Characterization based symmetry tests and their asymptotic efficiencies," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 155-162.
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