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Least Trimmed Squares (LTS) Regression×Medianabsolutavvikelse (MAD) – estimering×
ÄmnesområdeStatistikStatistik
FamiljRegression modelRegression model
Ursprungsår19841974
UpphovspersonPeter J. RousseeuwHampel (influence-curve treatment); classical robust statistics
TypRobust linear regressionRobust scale estimator
UrsprungskällaRousseeuw, 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 ↗
AliasLTS, least trimmed squares regression, trimmed least squares, robust regressionmedian absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini
Närliggande55
SammanfattningLeast 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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ScholarGateJämför metoder: Least Trimmed Squares · MAD Estimation. Hämtad 2026-06-19 från https://scholargate.app/sv/compare