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A note on the two-sample mean problem based on jackknife empirical likelihood

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  • Xinqi Wu
  • Sanguo Zhang
  • Qingzhao Zhang

Abstract

In this article, we employ the jackknife empirical likelihood (JEL) method to construct the confidence regions for the difference of the means of two d-dimensional samples. Compared with traditional EL for the two-sample mean problem, JEL is extremely simpler to use in practice and is more effective in computing. Based on the JEL ratio test, a version of Wilks’ theorem is developed. Furthermore, to improve the coverage accuracy of confidence regions, a Bartlett correction is applied. The effectiveness of the proposed method is demonstrated by a simulation study and a real data analysis.

Suggested Citation

  • Xinqi Wu & Sanguo Zhang & Qingzhao Zhang, 2017. "A note on the two-sample mean problem based on jackknife empirical likelihood," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(16), pages 7827-7836, August.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:16:p:7827-7836
    DOI: 10.1080/03610926.2015.1024864
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