Three points method for searching the best least absolute deviations plane

DOI10.1016/j.amc.2009.06.023zbMath1176.65017OpenAlexW2015653412MaRDI QIDQ734853

Robert Cupec, Kristian Sabo, Ratko Grbić, Rudolf Scitovski

Publication date: 14 October 2009

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2009.06.023

zbMATH Keywords

LADleast absolute deviations\(l_1\)-norm approximationweighted medium problem

Mathematics Subject Classification ID

Numerical aspects of computer graphics, image analysis, and computational geometry (65D18)

Related Items (7)

Weighted Median of the Data in Solving Least Absolute Deviations Problems ⋮ Application of growth functions in the prediction of live weight of domestic animals ⋮ One-dimensional center-based l 1-clustering method ⋮ Data clustering for circle detection ⋮ Searching for a best least absolute deviations solution of an overdetermined system of linear equations motivated by searching for a best least absolute deviations hyperplane on the basis of given data ⋮ Least absolute deviations problem for the Michaelis-Menten function ⋮ Center-based l1–clustering method

Uses Software

• KELLEY

Cites Work

• Weighted median algorithms for \(L_ 1\) approximation
• On orthogonal linear \(\ell_1\) approximation
• Locating lines and hyperplanes. Theory and algorithms
• Approximating surfaces by moving total least squares method
• Anchored hyperplane location problems
• Properties of three-dimensional median line location models
• Direct search methods: Then and now
• Dealing with the multiplicity of solutions of the \(\ell _{1}\) and \(\ell _{\infty }\) regression models
• On the Gauss-Newton method for l1 orthogonal distance regression
• A new descent algorithm for the least absolute value regression problem
• Inverse Problem Theory and Methods for Model Parameter Estimation
• Least‐squares problems for Michaelis–Menten kinetics
• THE BEST LEAST ABSOLUTE DEVIATIONS LINE – PROPERTIES AND TWO EFFICIENT METHODS FOR ITS DERIVATION
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