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Least Trimmed Squares (LTS) 回帰分析×ロバストANOVA(ウェルチとトリム平均)×
分野統計学統計学
系統Regression modelRegression model
提唱年19841951
提唱者Peter J. RousseeuwWelch (1951); robust trimmed-mean approach popularised by Wilcox
種類Robust linear regressionRobust one-way analysis of variance
原典Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗Welch, B. L. (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336. DOI ↗
別名LTS, least trimmed squares regression, trimmed least squares, robust regressionWelch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean)
関連55
概要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 the sum of only the h smallest squared residuals, which gives it a breakdown point of up to 50% and reliable estimates on data heavily contaminated by outliers.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.
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ScholarGate手法を比較: Least Trimmed Squares · Robust ANOVA. 2026-06-19に以下より取得 https://scholargate.app/ja/compare