29 – Generalized Additive, Varying Coefficient, and Stochastic Models
Variable Selection in Generalized Additive Mixed Models
Ahmet Sezer
Anadolu University
Cüneyt Toyganözü
Suleyman Demirel University
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 smoothing splines and minimize the sum of squared errors subject to an additive penalty of spline functions. We propose stepwise selection procedures for generalized additive models using penalized quasilikelihood.