Confronta i metodi

	Regression con Minimi Quadrati Trimmatizzati (Least Trimmed Squares, LTS)	Regressione dei Minimi Quadrati Mediani (LMS)
Campo	Statistica	Statistica
Famiglia	Regression model	Regression model
Anno di origine	1984	1984
Ideatore	Peter J. Rousseeuw	Peter J. Rousseeuw
Tipo	Robust linear regression	Robust linear regression
Fonte seminale	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.
Alias	LTS, least trimmed squares regression, trimmed least squares, robust regression	LMS, least median of squares regression, en küçük medyan kareler (LMS)
Correlati	5	5
Sintesi	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.	Least Median of Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of minimising the sum of squared residuals like ordinary least squares, it minimises the median of the squared residuals, which lets the fit resist contamination by up to roughly 50% outliers.