Порівняння методів

	Регресія найменших медіан квадратів (LMS)	Квантильна регресія
Галузь	Статистика	Економетрика
Родина	Regression model	Regression model
Рік появи	1984	1978
Автор методу	Peter J. Rousseeuw	Koenker & Bassett
Тип	Robust linear regression	Conditional quantile regression
Основоположне джерело	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.
Інші назви	LMS, least median of squares regression, en küçük medyan kareler (LMS)	conditional quantile regression, regression quantiles, Kantil Regresyon
Пов'язані	5	5
Підсумок	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.