The determination of a “least quantile of squares regression line” for all quantiles. (English) Zbl 0900.62351
Summary: Least median of squares regression has shown to be an extremely useful tool in robust regression analysis. In this note, we extend this concept to least quantile of squares regression, and propose a polynomial algorithm that finds simultaneously an estimator for each quantile. This leads to a proposal of a robust minimum scale regression line and a polynomial algorithm for its determination.
MSC:
| 62J05 | Linear regression; mixed models |
| 62J99 | Linear inference, regression |
| 62G07 | Density estimation |
Keywords:
Least median of squares regression; Robust regression; Sweep-line technique; Minquantile optimizationReferences:
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