विधियों की तुलना करें

	थेल-सेन अनुमानक	साधारण न्यूनतम वर्ग (OLS) समाश्रयण
क्षेत्र	सांख्यिकी	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1968	2019
प्रवर्तक	Henri Theil (1950); P. K. Sen (1968)	Wooldridge (textbook treatment); classical least squares
प्रकार	Robust linear regression	Linear regression
मौलिक स्रोत	Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
उपनाम	Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
संबंधित	6	5
सारांश	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%.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).