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	Least Trimmed Squares (LTS) रिग्रेशन	थेल-सेन अनुमानक
क्षेत्र	सांख्यिकी	सांख्यिकी
परिवार	Regression model	Regression model
उद्भव वर्ष	1984	1968
प्रवर्तक	Peter J. Rousseeuw	Henri Theil (1950); P. K. Sen (1968)
प्रकार	Robust linear regression	Robust linear regression
मौलिक स्रोत	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.	Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389.
उपनाम	LTS, least trimmed squares regression, trimmed least squares, robust regression	Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator
संबंधित	5	6
सारांश	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.	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%.