稳健与分位数
18 种方法属于此方法族。
精选
异方差稳健 (HC) 标准误Heteroscedasticity-robust standard errors are a correction to the covariance matrix of an OLS regression that yields valid inference when the error variance is not constant. IntrodHuber回归Huber regression is a robust linear regression method, introduced by Peter J. Huber in 1964, that resists the influence of outliers by treating small and large residuals differentl最小裁剪平方和（LTS）回归Least Trimmed Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of fitting all residuals, it estimates the coefficients by minimising tM估计量（稳健回归）M-estimators are a robust generalisation of maximum likelihood estimation, formalised in the work of Peter J. Huber (Huber & Ronchetti, 2009). Instead of squaring every residual, tMM估计量稳健回归The MM-estimator is a robust linear regression method introduced by Victor J. Yohai in 1987. It combines the high breakdown point of an S-estimator with the high efficiency of an M分位数回归（非参数变体）Quantile regression, introduced by Koenker and Bassett in 1978, models a chosen conditional quantile (such as the median or the 25th and 75th percentiles) of a continuous outcome r
阅读路径
本主题被引用最多的基础方法，按其提出的先后顺序排列——若您初次接触，不妨从这里开始。