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稳健简单线性回归×Theil-Sen 估计器×
领域统计学统计学
方法族Regression modelRegression model
起源年份1964-19871968
提出者Peter J. Huber (M-estimators, 1964); Rousseeuw & Leroy (practical framework, 1987)Henri Theil (1950); P. K. Sen (1968)
类型Robust linear regressionRobust linear regression
开创性文献Rousseeuw, P. J., & Leroy, A. M. (1987). Robust Regression and Outlier Detection. John Wiley & Sons. ISBN: 978-0471852339Sen, 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robust SLR, M-estimator simple regression, outlier-resistant simple regression, robust bivariate regressionTheil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator
相关66
摘要Robust simple linear regression fits a straight line through bivariate data using loss functions or weighting schemes that down-weight outliers, producing slope and intercept estimates that are far less sensitive to extreme observations than ordinary least squares while remaining easy to interpret.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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  3. PUBLISHED

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ScholarGate方法对比: Robust Simple linear regression · Theil-Sen Estimator. 于 2026-06-18 检索自 https://scholargate.app/zh/compare