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| انحدار المربعات الصغرى المشذبة (LTS)× | انحدار الكوانتيل× | |
|---|---|---|
| المجال≠ | الإحصاء | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1984 | 1978 |
| صاحب الطريقة≠ | Peter J. Rousseeuw | Koenker & Bassett |
| النوع≠ | Robust linear regression | Conditional quantile regression |
| المصدر التأسيسي≠ | Rousseeuw, 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 البديلة≠ | LTS, least trimmed squares regression, trimmed least squares, robust regression | conditional quantile regression, regression quantiles, Kantil Regresyon |
| ذات صلة | 5 | 5 |
| الملخص≠ | 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. | 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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