পদ্ধতির তুলনা করুন

	Least Trimmed Squares (LTS) Regression	Theil-Sen Estimator
ক্ষেত্র	পরিসংখ্যান	পরিসংখ্যান
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1984	1968
প্রবর্তক	Peter J. Rousseeuw	Henri Theil (1950); P. K. Sen (1968)
ধরন	Robust linear regression	Robust linear regression
মৌলিক উৎস	Rousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880.	Sen, P. K. (1968). Estimates of the Regression Coefficient Based on Kendall's Tau. Journal of the American Statistical Association, 63(324), 1379-1389.
অপর নাম	LTS, least trimmed squares regression, trimmed least squares, robust regression	Theil-Sen Tahmincisi, Theil-Sen regression, median slope estimator, Sen's slope estimator
সম্পর্কিত	5	6
সারসংক্ষেপ	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.	The Theil-Sen estimator is a robust linear regression method that estimates the slope as the median of the slopes computed over all pairs of data points. Introduced by Henri Theil in 1950 and extended by P. K. Sen in 1968, it tolerates outliers in the response with a breakdown point of about 29%.