JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 29
Type: Contributed
Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #306162
Title: Variable Selection in Generalized Additive Mixed Models
Author(s): Ahmet Sezer*+ and Cüneyt Toyganözü
Companies: Anadolu University and Suleyman Demirel University
Address: Fen Fakultesi, Eskisehir, , Turkey
Keywords: Variable selection ; semiparametric mixed models ; Penalized Quasilikelihood

Identifying the subset of the important variables is of special importance in multivariate regression. In this study we are interested in selecting significant covariates in semiparametric mixed modelling. Variable selection procedure considers both nonparametric and parametric component. We approximate nonparametric component by polynomial splines and minimize the sum of squared errors subject to an additive penalty of spline functions. Semiparametric generalized likelihood ratio test is proposed to select significant variables in the nonparametric component. We show that semiparametric likelihood ratio test statistics follow Chi-squared distribution. Monte Carlo simulation studies are also conducted to examine the finite sample performance of the proposed procedure

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.