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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23405

Title: Variable selection with nonnegative garrote in additive models
Authors: Verhasselt, Anneleen
Issue Date: 2009
Citation: Proceedings of the 16th European Young Statisticians Meeting,p. 23-25
Abstract: The nonnegative garrote was originally proposed by Breiman (1995) for variable selection in a multiple linear regression context. The procedure starts from the ordinary least squares estimator (OLS) and shrinks or puts some coefficients of the OLS equal to zero. In this work we consider a functional additive model and use P-splines as a basic estimation method. P-splines were introduced by Eilers and Marx (1996) as a univariate flexible smoothing technique. We therefore combine this technique with a backfitting algorithm to deal with the additive modelling. A nonnegative garrote step then takes care of the variable selection issue.
URI: http://hdl.handle.net/1942/23405
Category: C2
Type: Proceedings Paper
Appears in Collections: Research publications

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