Journal
STATISTICS AND COMPUTING
Volume 22, Issue 2, Pages 545-561Publisher
SPRINGER
DOI: 10.1007/s11222-011-9246-z
Keywords
Single-index models; P-splines; Choice of link function; Variable selection; Nonparametric estimation of link function
Ask authors/readers for more resources
Nonparametric methods for the estimation of the link function in generalized linear models are able to avoid bias in the regression parameters. But for the estimation of the link typically the full model, which includes all predictors, has been used. When the number of predictors is large these methods fail since the full model cannot be estimated. In the present article a boosting type method is proposed that simultaneously selects predictors and estimates the link function. The method performs quite well in simulations and real data examples.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available