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Abstract Details
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Activity Number:
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333
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #303452 |
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Title:
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Generalized Varying Coefficient Models: A Smooth Variable Selection Technique
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Author(s):
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Anneleen Verhasselt*+
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Companies:
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Katholieke Universiteit Leuven
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Address:
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Department of Mathematics, Heverlee, 3001, Belgium
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Keywords:
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Abstract:
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We consider nonparametric smoothing and variable selection in generalized varying coefficient models. Generalized varying coecient models are commonly used for analyzing the time-dependent effects of covariates on responses, which are not necessary continuous, but for example counts or categories. We present the P-spline estimator in this context and show its estimation consistency for a diverging number of knots, 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 real data example.
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