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انحدار المربعات الصغرى المشذبة (LTS)×انحدار الكوانتيل×
المجالالإحصاءالاقتصاد القياسي
العائلةRegression modelRegression model
سنة النشأة19841978
صاحب الطريقةPeter J. RousseeuwKoenker & Bassett
النوعRobust linear regressionConditional quantile regression
المصدر التأسيسيRousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
الأسماء البديلةLTS, least trimmed squares regression, trimmed least squares, robust regressionconditional quantile regression, regression quantiles, Kantil Regresyon
ذات صلة55
الملخصLeast 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.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.
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ScholarGateقارن الطرق: Least Trimmed Squares · Quantile Regression. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare