Mixed integer second-order cone programming formulations for variable selection in linear regression

•AIC/BIC minimization, and adjusted R2 maximization problems are considered.•These problems are formulated as mixed integer second-order cone programming problems.•Experiments shows results of better quality than obtained by stepwise regression. This study concerns a method of selecting the best sub...

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Veröffentlicht in:	European journal of operational research Jg. 247; H. 3; S. 721 - 731
Hauptverfasser:	Miyashiro, Ryuhei, Takano, Yuichi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 16.12.2015 Elsevier Sequoia S.A
Schlagworte:	Decision making models Information criterion Integer programming Mathematical problems Multiple linear regression Regression analysis Second-order cone programming Studies Variable selection Variables Integer programming Multiple linear regression Information criterion Second-order cone programming Variable selection
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
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