Salīdzināt metodes

	Regresija ar mazāko kvadrātisko mediānu (LMS)	Kvantīļu regresija
Nozare	Statistika	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1984	1978
Autors	Peter J. Rousseeuw	Koenker & Bassett
Tips	Robust linear regression	Conditional quantile regression
Pirmavots	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Citi nosaukumi	LMS, least median of squares regression, en küçük medyan kareler (LMS)	conditional quantile regression, regression quantiles, Kantil Regresyon
Saistītās	5	5
Kopsavilkums	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.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.