Depth-based weighted empirical likelihood and general estimating equations

Yunlu Jiang, Shaoli Wang, Wenxiu Ge and Xueqin Wang

Journal of Nonparametric Statistics, 2011, vol. 23, issue 4, 1051-1062

Abstract: In this paper, we link the depth-based weighted empirical likelihood (WEL) with general estimating equations to produce a robust estimation of parameters for contaminated data with auxiliary information about the parameters. Such auxiliary information can be expressed through a group of functionally independent general estimating equations. Under general conditions, asymptotic properties of the WEL estimator are established. Furthermore, we prove that the WEL ratio statistic is asymptotically chi-squared distributed. Simulation studies are conducted to test the robustness of the WEL estimator. Finally, we apply the proposed method to analyse the gilgai survey data.

Date: 2011
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DOI: 10.1080/10485252.2011.594510

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