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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16130

Title: Generalized varying coefficient models: a smooth variable selection technique
Authors: VERHASSELT, Anneleen
Issue Date: 2014
Citation: Statistica sinica, 24 (1), p. 147-171
Abstract: We consider nonparametric smoothing and variable selection in generalized varying coefficient models. Generalized varying coefficient models are commonly used for analyzing the time-dependent effects of covariates on responses that are not necessary continuous, for example counts or categories. We present the Pspline estimator in this context and show its estimation consistency for a diverging number of knots (or B-spline basis functions), by using an approximation of the link function. The combination of P-splines with nonnegative garrote (which is a variable selection method) leads to good estimation and variable selection. The method is illustrated with a simulation study and a data example.
Notes: Verhasselt, A (reprint author), Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, CenStat Agoralaan Bldg D 3590, Diepenbeek, Belgium. anneleen.verhasselt@uhasselt.be
URI: http://hdl.handle.net/1942/16130
DOI: 10.5705/ss.2011.168
ISI #: 000350178100008
ISSN: 1017-0405
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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