An algorithm for a least absolute value regression problem with bounds on the parameters

DOI10.1016/0096-3003(80)90049-1zbMath0445.65061OpenAlexW1972324478MaRDI QIDQ1145473

Ronald D. Armstrong, Mabel Tam Kung

Publication date: 1980

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

Full work available at URL: https://doi.org/10.1016/0096-3003(80)90049-1

zbMATH Keywords

algorithmcomputational resultsbounds on the parametersleast absolute value regression problem

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Numerical mathematical programming methods (65K05) Linear programming (90C05)

Related Items (1)

Computational Algorithms for Calculating Least Absolute Value and Chebyshev Estimates for Multiple Regression

Uses Software

• Algorithm 478

Cites Work

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• Optimal Estimation of Executive Compensation by Linear Programming
• A revised simplex algorithm for the absolute deviation curve fitting problem
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• A Branch-and-Bound Solution of a Restricted Least Squares Problem
• An Algorithm for a Restricted Discrete Approximation Problem in the $L_1 $ Norm
• An Algorithm for Solving Interval Linear Programming Problems
• An Efficient Algorithm for Discrete $l_1$ Linear Approximation with Linear Constraints
• A Restricted Least Squares Problem
• Inequality Restrictions in Regression Analysis
• The 1972 Wald Lecture Robust Statistics: A Review
• Discrete approximation in the L1 norm
• An Improved Algorithm for Discrete $l_1 $ Linear Approximation
• Optimality and Degeneracy in Linear Programming

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