Comparar métodos

	Regresión por Mínimos Cuadrados Recortados (LTS)	Regresión por Mínima Mediana de los Cuadrados (LMS)
Campo	Estadística	Estadística
Familia	Regression model	Regression model
Año de origen	1984	1984
Autor original	Peter J. Rousseeuw	Peter J. Rousseeuw
Tipo	Robust linear regression	Robust linear regression
Fuente seminal	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.
Alias	LTS, least trimmed squares regression, trimmed least squares, robust regression	LMS, least median of squares regression, en küçük medyan kareler (LMS)
Relacionados	5	5
Resumen	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.