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Vähiten katkaistujen neliöiden (LTS) regressio×Robust ANOVA (Welch & Trimmed Mean)×
TieteenalaTilastotiedeTilastotiede
MenetelmäperheRegression modelRegression model
Syntyvuosi19841951
KehittäjäPeter J. RousseeuwWelch (1951); robust trimmed-mean approach popularised by Wilcox
TyyppiRobust linear regressionRobust one-way analysis of variance
AlkuperäislähdeRousseeuw, 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 ↗
RinnakkaisnimetLTS, least trimmed squares regression, trimmed least squares, robust regressionWelch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean)
Liittyvät55
TiivistelmäLeast 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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ScholarGateVertaile menetelmiä: Least Trimmed Squares · Robust ANOVA. Haettu 2026-06-19 osoitteesta https://scholargate.app/fi/compare