Time- and Space-Efficient Algorithms for Least Median of Squares Regression
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Publication:3771429
DOI10.2307/2288788zbMath0633.62061OpenAlexW4246226343MaRDI QIDQ3771429
J. Michael Steele, Diane L. Souvaine
Publication date: 1987
Full work available at URL: https://doi.org/10.2307/2288788
algorithmsglobal optimizationarrangement of linesaffine dualityarrangement searchingleast median of squared residuals regression linesweep-line technique
Linear regression; mixed models (62J05) Probabilistic methods, stochastic differential equations (65C99)
Related Items (13)
The determination of a ``least quantile of squares regression line for all quantiles ⋮ Parallel algorithms for least median of squares regression ⋮ Some Early Work on the Duality Between Points and Lines ⋮ A practical approximation algorithm for the LTS estimator ⋮ On the least trimmed squares estimator ⋮ Least quantile regression via modern optimization ⋮ An algorithm for computing exact least-trimmed squares estimate of simple linear regression with constraints ⋮ On the implementation of LIR: the case of simple linear regression with interval data ⋮ Efficient randomized algorithms for robust estimation of circular arcs and aligned ellipses ⋮ The feasible set algorithm for least median of squares regression ⋮ A practical approximation algorithm for the LMS line estimator ⋮ BACON: blocked adaptive computationally efficient outlier nominators. ⋮ A Monte Carlo comparison of several high breakdown and efficient estimators
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