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Erschienen in:
1999 | OriginalPaper | Buchkapitel
Selection of Cut Points in Generalized Additive Models
verfasst von : Francesco Mola
Erschienen in: Classification and Data Analysis
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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This paper offers, in the framework of generalized additive models (GAM), a proposal of a cut point selection for GAM smoothers that stems out of the CART like regression tree procedures. The proposal allows to find a parsimonious bin smoother (regressogram), a new smoother based on the well known loess smoother, and provides, moreover, the user with an additional information inherited from the regression tree methodology. The problem of the choice of span parameter is considered too.