Robust Estimation in the Errors-in-Variables Model
定义了正交回归M估计和S估计，证明其在椭圆变量含误差模型下的一致性和稳健性，并给出计算算法和蒙特卡洛实验结果。
Orthogonal regression analogues of M estimates of regression, called here orthogonal regression M estimates, are defined. These estimates are shown to be consistent at elliptical errors-in-variables models and robust, if the corresponding loss function is bounded. The orthogonal regression analogues of regression scale estimates, called here orthogonal regression S estimates, are considered as well. In particular, they provide a robust estimate for the scale of the orthogonal residuals, a crucial quantity in the computation of orthogonal regression M estimates. Finally we present an algorithm for computing orthogonal regression S and M estimates and the results of a small Monte Carlo experiment.