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Connections Between Optimisation-Based Regressor Selection and Analysis of Variance
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2006 (English)In: Proceedings of Reglermöte 2006, 2006Conference paper, Published paper (Other academic)
Abstract [en]

Earlier contributions have shown that Analysis of Variance (ANOVA) can be successfully used for finding good regressors for nonlinear models in a nonlinear black-box system identification context. In this paper, it is shown that the ANOVA problem can be recast as an optimisation problem. A modified, convex version of the ANOVA optimisation problem is then proposed, and it turns out that it is closely related to the nn-garrote method, respectively. In the case of balanced data, it is also shown that the method has a nice orthogonality property in the sense that different groups of parameters can be computed independently.

Place, publisher, year, edition, pages
2006.
Keyword [en]
Regressor selection, ANOVA, 1-norm, Lasso, Nn-garrote
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-36931Local ID: 33078OAI: oai:DiVA.org:liu-36931DiVA: diva2:257780
Conference
Reglermöte 2006, Stockholm, Sweden, May, 2006
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-02-26

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Roll, JacobLind, IngelaLjung, Lennart

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