An \(L_{1}\) estimation algorithm with degeneracy and linear constraints.

DOI10.1016/S0167-9473(01)00049-4zbMath1119.65306OpenAlexW2042092375WikidataQ56698202 ScholiaQ56698202MaRDI QIDQ1608621

Mingren Shi, Mark A. Lukas

Publication date: 8 August 2002

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

Full work available at URL: https://doi.org/10.1016/s0167-9473(01)00049-4

Mathematics Subject Classification ID

Related Items (4)

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 ⋮ Numerical algorithms for estimation and calculation of parameters in modeling pest population dynamics and evolution of resistance ⋮ Sensitivity analysis of constrained linear \(L_1\) regression: perturbations to response and predictor variables ⋮ Sensitivity analysis of constrained linear \(L_1\) regression: Perturbations to constraints, addition and deletion of observations

Uses Software

• AS 74
• LPASL1
• Algorithm 551

Cites Work

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• A new LAD curve-fitting algorithm: Slightly overdetermined equation systems in \(L_ 1\)
• Primal-dual interior point approach for computing \(l_ 1\)-solutions and \(l_ \infty\)-solutions of overdetermined linear systems
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• Linear Programming Techniques for Regression Analysis
• A revised simplex algorithm for the absolute deviation curve fitting problem
• Algorithm 552: Solution of the Constrained I ₁ Linear Approximation Problem [F4]
• Linearly Constrained Discrete I ₁ Problems
• Algorithm 563: A Program for Linearly Constrained Discrete I ₁ Problems
• Least Absolute Deviations Curve-Fitting
• Using the $L_2 $-Estimator in $L_1 $-Estimation
• An Algorithm for a Restricted Discrete Approximation Problem in the $L_1 $ Norm
• Minimization Techniques for Piecewise Differentiable Functions: The $l_1$ Solution to an Overdetermined Linear System
• An Efficient Algorithm for Discrete $l_1$ Linear Approximation with Linear Constraints
• The Linear l₁ Estimator and the Huber M-Estimator
• A New Finite Continuation Algorithm for Linear Programming
• A Finite Smoothing Algorithm for Linear $l_1 $ Estimation
• An Improved Algorithm for Discrete $l_1 $ Linear Approximation

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