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S估计量稳健回归×Theil-Sen 估计器×
领域统计学统计学
方法族Regression modelRegression model
起源年份19841968
提出者Rousseeuw & Yohai (1984)Henri Theil (1950); P. K. Sen (1968)
类型Robust linear regressionRobust linear regression
开创性文献Rousseeuw, P. J. & Yohai, V. J. (1984). Robust Regression by Means of S-Estimators. In Robust and Nonlinear Time Series Analysis (Lecture Notes in Statistics, Vol. 26, pp. 256-272). Springer. DOI ↗Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389. DOI ↗
别名S-estimation, robust S-regression, S-Tahmin EdiciTheil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator
相关56
摘要The S-estimator is a robust linear-regression method, introduced by Rousseeuw and Yohai in 1984, that estimates the coefficients by minimising a robust M-estimate of the residual scale rather than the variance of the residuals. By driving down a bounded measure of residual spread it can attain a breakdown point of up to 50%, so it stays reliable even when a large share of the data are outliers, and it provides the first stage of the well-known MM-estimator.The Theil-Sen estimator is a robust linear regression method that estimates the slope as the median of the slopes computed over all pairs of data points. Introduced by Henri Theil in 1950 and extended by P. K. Sen in 1968, it tolerates outliers in the response with a breakdown point of about 29%.
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ScholarGate方法对比: S-Estimator · Theil-Sen Estimator. 于 2026-06-19 检索自 https://scholargate.app/zh/compare