A fast algorithm for non-negativity model selection

An efficient optimization algorithm for identifying the best least squares regression model under the condition of non-negative coefficients is proposed. The algorithm exposits an innovative solution via the unrestricted least squares and is based on the regression tree and branch-and-bound techniqu...

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Veröffentlicht in:	Statistics and computing Jg. 23; H. 3; S. 403 - 411
Hauptverfasser:	Gatu, Cristian, Kontoghiorghes, Erricos John
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Boston Springer US 01.05.2013
Schlagworte:	Algorithms Artificial Intelligence Computation Effectiveness Least squares method Mathematical models Mathematics and Statistics Probability and Statistics in Computer Science Regression Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs Strategy Non-negative least squares Subset selection Branch-and-bound algorithms
ISSN:	0960-3174, 1573-1375
Online-Zugang:	Volltext
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