Variable Selection in Additive Models Using P-Splines

作者：Antoniadis Anestis^*; Gijbels Irene; Verhasselt Anneleen

来源：Technometrics, 2012, 54(4): 425-438.

DOI：10.1080/00401706.2012.726000

• Additive modeling
• Nonnegative garrote
• Nonparametric smoothing
• Penalized spline regression
• Selection of variables

This article extends the nonnegative garrote method to a component selection method in a nonparametric additive model in which each univariate function is estimated with P-splines. We also establish the consistency of the procedure. An advantage of P-splines is that the fitted function is represented in a rather small basis of B-splines. A numerical study illustrates the finite-sample performance of the method and includes a comparison with other methods. The nonnegative garrote method with P-splines has the advantage of being computationally fast and performs, with an appropriate parameter selection procedure implemented, overall very well. Real data analysis leads to interesting findings. Supplementary materials for this article (technical proofs, additional numerical results, R code) are available online.

• 出版日期2012-11