Bounded-Influence Rank Regression: A One-Step Estimator Based on Wilcoxon Scores
有界影响秩回归:基于 Wilcoxon 得分的一步估计量
The Krasker-Welsch (1982) approach to bounding influence is merged with rank regression. I propose a one-step estimator that is analogous to Bickel's (1975) one-step M estimator of Type 1 but uses weights that depend on the design vector and the residuals to reduce the influence of outliers. In fact, the standardized sensitivity of the estimator is made equal to a prechosen constant. It is based, however, on a second-derivative approximation to a dispersion surface that is…