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Regrese nejmenších ořezaných čtverců (Least Trimmed Squares, LTS)×Odhad mediánovou absolutní odchylkou (MAD)×
OborStatistikaStatistika
RodinaRegression modelRegression model
Rok vzniku19841974
TvůrcePeter J. RousseeuwHampel (influence-curve treatment); classical robust statistics
TypRobust linear regressionRobust scale estimator
Původní zdrojRousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗
Další názvyLTS, least trimmed squares regression, trimmed least squares, robust regressionmedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini
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.Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result.
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ScholarGatePorovnat metody: Least Trimmed Squares · MAD Estimation. Získáno 2026-06-18 z https://scholargate.app/cs/compare