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

Xinqi Wu, Sanguo Zhang and Qingzhao Zhang

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 16, 7827-7836

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.

Date: 2017
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DOI: 10.1080/03610926.2015.1024864

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