Robust Regression Using Repeated Medians
提出重复中位数算法，通过嵌套中位数替代均值来构建稳健回归估计，能抵抗近半数异常值的影响，在对称误差下无偏且高效。
The repeated median algorithm is a robustified U-statistic in which nested medians replace the single mean. Unlike many generalizations of the univariate median, repeated median estimates maintain the high 50% breakdown value and can resist the effects of outliers even when they comprise nearly half of the data. For bivariate linear regression with symmetric errors, repeated median estimates are unbiased and Fisher consistent, and their efficiency under Gaussian sampling can be comparable to the efficiency of the univariate median.