Scalable holistic linear regression

DOI10.1016/j.orl.2020.02.008OpenAlexW3006935723MaRDI QIDQ2183189

Michael Lingzhi Li, Dimitris J. Bertsimas

Publication date: 26 May 2020

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1902.03272

zbMATH Keywords

mixed-integer optimizationholistic linear regressionmulticollinearity and significance in linear regression

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Related Items (3)

Learning sparse nonlinear dynamics via mixed-integer optimization ⋮ Rejoinder: ``Sparse regression: scalable algorithms and empirical performance ⋮ Bilevel cutting-plane algorithm for cardinality-constrained mean-CVaR portfolio optimization

Uses Software

• UCI-ml

Cites Work

• Unnamed Item
• Characterization of the equivalence of robustification and regularization in linear and matrix regression
• Mixed integer quadratic optimization formulations for eliminating multicollinearity based on variance inflation factor
• OR Forum—An Algorithmic Approach to Linear Regression
• Asymptotic Normality and Consistency of the Least Squares Estimators for Families of Linear Regressions
• A Biometrics Invited Paper. The Analysis and Selection of Variables in Linear Regression
• BEST SUBSET SELECTION FOR ELIMINATING MULTICOLLINEARITY

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