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ロバストANOVA(ウェルチとトリム平均)×最小二乗法 (OLS) 回帰×Theil-Sen推定量×
分野統計学計量経済学統計学
系統Regression modelRegression modelRegression model
提唱年195120191968
提唱者Welch (1951); robust trimmed-mean approach popularised by WilcoxWooldridge (textbook treatment); classical least squaresHenri Theil (1950); P. K. Sen (1968)
種類Robust one-way analysis of varianceLinear regressionRobust linear regression
原典Welch, B. L. (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389. DOI ↗
別名Welch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuTheil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator
関連556
概要Robust ANOVA compares the central tendency of three or more groups when the classical assumptions of normality and equal variances fail. It combines Welch's heteroscedasticity-adjusted statistic, introduced by Welch in 1951, with trimmed-mean tests advanced by Wilcox, giving reliable comparisons in the presence of outliers and unequal group spreads.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).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手法を比較: Robust ANOVA · OLS Regression · Theil-Sen Estimator. 2026-06-18に以下より取得 https://scholargate.app/ja/compare