Сравнение методов

	Регрессия по методу наименьших усеченных квадратов (LTS)	Регрессия по методу наименьших медиан квадратов (LMS)
Область	Статистика	Статистика
Семейство	Regression model	Regression model
Год появления	1984	1984
Автор метода	Peter J. Rousseeuw	Peter J. Rousseeuw
Тип	Robust linear regression	Robust linear regression
Основополагающий источник	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.
Другие названия	LTS, least trimmed squares regression, trimmed least squares, robust regression	LMS, least median of squares regression, en küçük medyan kareler (LMS)
Связанные	5	5
Сводка	Least Trimmed Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of fitting all residuals, it estimates the coefficients by minimising the sum of only the h smallest squared residuals, which gives it a breakdown point of up to 50% and reliable estimates on data heavily contaminated by outliers.	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.