Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/31055
Authors: 
Leitenstorfer, Florian
Tutz, Gerhard
Year of Publication: 
2006
Series/Report no.: 
Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 467
Abstract: 
In many applications it is known that the underlying smooth function is constrained to have a specific form. In the present paper, we propose an estimation method based on the regression spline approach, which allows to include concavity or convexity constraints in an appealing way. Instead of using linear or quadratic programming routines, we handle the required inequality constraints on basis coefficients by boosting techniques. Therefore, recently developed componentwise boosting methods for regression purposes are applied, which allow to control the restrictions in each iteration. The proposed approach is compared to several competitors in a simulation study. We also consider a real world data set.
Subjects: 
Shape constrained smoothing
Concavity
Regression splines
Boosting
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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