The determination of a ``least quantile of squares regression line for all quantiles

DOI10.1016/0167-9473(94)00059-RzbMath0900.62351OpenAlexW2037442322MaRDI QIDQ1350244

Emilio Carrizosa, Frank Plastria

Publication date: 27 February 1997

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(94)00059-r

zbMATH Keywords

Robust regressionLeast median of squares regressionMinquantile optimizationSweep-line technique

Mathematics Subject Classification ID

Density estimation (62G07) Linear regression; mixed models (62J05) Linear inference, regression (62J99)

Related Items

Formulas for the Exact LMS and LQS Estimators ⋮ Locating hyperplanes to fitting set of points: a general framework ⋮ On minquantile and maxcovering optimisation ⋮ On the implementation of LIR: the case of simple linear regression with interval data ⋮ Solving restricted line location problems via a dual interpretation ⋮ Applied regression analysis bibliography update 1994-97

Cites Work

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• Algorithms and complexity for least median of squares regression
• Parallel algorithms for least median of squares regression
• On minquantile and maxcovering optimisation
• On L1 and Chebyshev estimation
• Least Median of Squares Regression
• Computing Least Median of Squares Regression Lines and Guided Topological Sweep
• Time- and Space-Efficient Algorithms for Least Median of Squares Regression
• On minimax optimization problems

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