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Extrapolation techniques in U-statistic variance estimation

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  • Qing Wang

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.

Suggested Citation

  • Qing Wang, 2017. "Extrapolation techniques in U-statistic variance estimation," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(17), pages 8387-8400, September.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:17:p:8387-8400
    DOI: 10.1080/03610926.2016.1179760
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