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Regrese nejmenších ořezaných čtverců (Least Trimmed Squares, LTS)×Robustní ANOVA (Welch & Ořezaný průměr)×
OborStatistikaStatistika
RodinaRegression modelRegression model
Rok vzniku19841951
TvůrcePeter J. RousseeuwWelch (1951); robust trimmed-mean approach popularised by Wilcox
TypRobust linear regressionRobust one-way analysis of variance
Původní zdrojRousseeuw, 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 ↗
Další názvyLTS, least trimmed squares regression, trimmed least squares, robust regressionWelch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean)
Příbuzné55
ShrnutíLeast 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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ScholarGatePorovnat metody: Least Trimmed Squares · Robust ANOVA. Získáno 2026-06-18 z https://scholargate.app/cs/compare