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Jackknife empirical likelihood method for testing the equality of two variances

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  • Ying-Ju Chen
  • Wei Ning
  • Arjun K. Gupta

Abstract

In this paper, we propose a nonparametric method based on jackknife empirical likelihood ratio to test the equality of two variances. The asymptotic distribution of the test statistic has been shown to follow χ-super-2 distribution with the degree of freedom 1. Simulations have been conducted to show the type I error and the power compared to Levene's test and F test under different distribution settings. The proposed method has been applied to a real data set to illustrate the testing procedure.

Suggested Citation

  • Ying-Ju Chen & Wei Ning & Arjun K. Gupta, 2015. "Jackknife empirical likelihood method for testing the equality of two variances," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(1), pages 144-160, January.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:1:p:144-160
    DOI: 10.1080/02664763.2014.938225
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    References listed on IDEAS

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    1. Arjun Gupta & Solomon Harrar & Leandro Pardo, 2007. "On testing homogeneity of variances for nonnormal models using entropy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(2), pages 245-261, August.
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    Cited by:

    1. Yongli Sang, 2021. "A Jackknife Empirical Likelihood Approach for Testing the Homogeneity of K Variances," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(7), pages 1025-1048, October.

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