Extrapolation techniques in U-statistic variance estimation

Qing Wang

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 17, 8387-8400

Abstract: This article considers the problem of variance estimation of a U-statistic. Following the proposal of a linearly extrapolated variance estimator in Wang and Chen (2015), we consider a second-order extrapolation technique and devise a variance estimator that is nearly second-order unbiased. Simulation studies confirm that the second-order extrapolated variance estimator has smaller bias than the linearly extrapolated variance estimator and the jackknife variance estimator across a wide selection of distributions. In addition, the proposal also yields a smaller mean squared error than its counterparts. In the end, we discuss the advantages of the proposed variance estimator in regression analysis and model selection.

Date: 2017
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DOI: 10.1080/03610926.2016.1179760

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