JSM 2011 Online Program

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Abstract Details

Activity Number: 156
Type: Topic Contributed
Date/Time: Monday, August 1, 2011 : 10:30 AM to 12:20 PM
Sponsor: International Chinese Statistical Association
Abstract - #302954
Title: P-Splines Regression Smoothing and Variable Selection
Author(s): Irene Gijbels*+
Companies: Katholieke Universiteit Leuven
Address: Celestijnenlaan 200B, B-3001 Leuven (Heverlee), International, B-3001 , Belgium
Keywords: P-splines regression ; variable selection ; regression models
Abstract:

In this talk we focus on penalized estimation in additive models and varying coefficient models. A main interest is also on variable selection for such models.

Particular attention goes to recent variable selection procedures such as grouped Lasso, grouped SCAD, COSSO, but also to the nonnegative garrote method introduced originally for variable selection in a multiple linear regression model. We show how the latter method combined with P-splines estimation leads to an estimation and variable consistent method in both the settings of additive models and varying coefficient models. The performances of this and other related selection procedures are investigated in a simulation study and illustrations on real data examples are provided.

In the additive varying coefficient model a uniform framework is presented and the various grouped regularization procedures are studied. A discussion on implementation issues and computational algorithms is provided, and a comparative simulation study is given.

This talk is based on joint works with Anestis Antoniadis, Sophie Lambert-Lacroix and Anneleen Verhasselt.


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