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On the weighted multivariate Wilcoxon rank regression estimate

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  • Zhou, Weihua
  • Wang, Jin

Abstract

Zhou (2010) introduced a multivariate Wilcoxon regression estimate which possesses some nice properties: computational ease, asymptotic normality and high efficiency. However, it is sensitive to the leverage points. To circumvent this problem, we propose a weighted multivariate Wilcoxon regression estimate. Under some regularity conditions, the asymptotic normality is established. We further study the robustness of the proposed estimate through the influence function. By properly choosing the weight functions, our results show that the corresponding estimate can have bounded influence function on both response and covariates.

Suggested Citation

  • Zhou, Weihua & Wang, Jin, 2011. "On the weighted multivariate Wilcoxon rank regression estimate," Statistics & Probability Letters, Elsevier, vol. 81(6), pages 704-713, June.
    • Handle: RePEc:eee:stapro:v:81:y:2011:i:6:p:704-713
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    References listed on IDEAS

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    1. Ollila E. & Oja H. & Koivunen V., 2003. "Estimates of Regression Coefficients Based on Lift Rank Covariance Matrix," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 90-98, January.
    2. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(2), pages 186-199, June.
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