विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| डब्ल्यू-एस्टिमेटर रोबस्ट रिग्रेशन (वेल्श / टुकी बिस्क्वेयर)× | साधारण न्यूनतम वर्ग (OLS) समाश्रयण× | थेल-सेन अनुमानक× | |
|---|---|---|---|
| क्षेत्र≠ | सांख्यिकी | अर्थमिति | सांख्यिकी |
| परिवार | Regression model | Regression model | Regression model |
| उद्भव वर्ष≠ | 1974 | 2019 | 1968 |
| प्रवर्तक≠ | Beaton & Tukey (bisquare weight); Welsch (Welsch weight) | Wooldridge (textbook treatment); classical least squares | Henri Theil (1950); P. K. Sen (1968) |
| प्रकार≠ | Robust regression (redescending M-estimator) | Linear regression | Robust linear regression |
| मौलिक स्रोत≠ | Beaton, A. E. & Tukey, J. W. (1974). The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data. Technometrics, 16(2), 147-185. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 | Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389. DOI ↗ |
| उपनाम≠ | Tukey bisquare M-estimator, Welsch M-estimator, redescending M-estimator, W-Tahmin Edici (Welsch / Tukey Bisquare) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator |
| संबंधित≠ | 4 | 5 | 6 |
| सारांश≠ | The W-estimator is a family of robust M-estimator variants for linear regression that use the Tukey bisquare and Welsch weight functions, introduced in the line of work going back to Beaton and Tukey (1974). Because its weights fall rapidly toward zero as a residual grows, it resists outliers more strongly than the Huber M-estimator. | 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). | 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%. |
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