Bandingkan kaedah

	Regresi Kuadran Median Terkecil (Least Median of Squares - LMS)	Regresi Kuantil
Bidang	Statistik	Ekonometrik
Keluarga	Regression model	Regression model
Tahun asal	1984	1978
Pengasas	Peter J. Rousseeuw	Koenker & Bassett
Jenis	Robust linear regression	Conditional quantile regression
Sumber perintis	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
Berkaitan	5	5
Ringkasan	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.