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	Regressione dei Minimi Quadrati Mediani (LMS)	Regressione quantilica
Campo	Statistica	Econometria
Famiglia	Regression model	Regression model
Anno di origine	1984	1978
Ideatore	Peter J. Rousseeuw	Koenker & Bassett
Tipo	Robust linear regression	Conditional quantile regression
Fonte seminale	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.
Alias	LMS, least median of squares regression, en küçük medyan kareler (LMS)	conditional quantile regression, regression quantiles, Kantil Regresyon
Correlati	5	5
Sintesi	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.