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Title: | Generalized varying coefficient models: a smooth variable selection technique | Authors: | VERHASSELT, Anneleen | Issue Date: | 2014 | Source: | 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 | Keywords: | generalized varying coefficient models; longitudinal data; nonparametric smoothing; P-splines; variable selection | Document URI: | http://hdl.handle.net/1942/16130 | ISSN: | 1017-0405 | e-ISSN: | 1996-8507 | DOI: | 10.5705/ss.2011.168 | ISI #: | 000350178100008 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2016 |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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Verhasselt 2014.pdf Restricted Access | 1.93 MB | Adobe PDF | View/Open Request a copy | |
13399.pdf | Non Peer-reviewed author version | 590.53 kB | Adobe PDF | View/Open |
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