Σύγκριση μεθόδων

	Εκτιμητής Theil-Sen	Παλινδρόμηση Ελαχίστων Ολοστρωμένων Τετραγώνων (Least Trimmed Squares - LTS)
Πεδίο	Στατιστική	Στατιστική
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1968	1984
Δημιουργός	Henri Theil (1950); P. K. Sen (1968)	Peter J. Rousseeuw
Τύπος	Robust linear regression	Robust linear regression
Θεμελιώδης πηγή	Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389.	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.
Εναλλακτικές ονομασίες	Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator	LTS, least trimmed squares regression, trimmed least squares, robust regression
Συναφείς	6	5
Σύνοψη	The Theil-Sen estimator is a robust linear regression method that estimates the slope as the median of the slopes computed over all pairs of data points. Introduced by Henri Theil in 1950 and extended by P. K. Sen in 1968, it tolerates outliers in the response with a breakdown point of about 29%.	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.