Porovnať metódy

	Regresia najmenšej mediánovej sumy štvorcov (LMS)	Regresia metódou najmenších štvorcov (OLS)
Odbor	Štatistika	Ekonometria
Rodina	Regression model	Regression model
Rok vzniku	1984	2019
Tvorca	Peter J. Rousseeuw	Wooldridge (textbook treatment); classical least squares
Typ	Robust linear regression	Linear regression
Pôvodný zdroj	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Ďalšie názvy	LMS, least median of squares regression, en küçük medyan kareler (LMS)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Príbuzné	5	5
Zhrnutie	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.	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).