Data-driven selection of the spline dimension in penalized spline regression

被引：15
|
作者：
Kauermann, Goeran [1 ]
Opsomer, Jean D. [2 ]
机构：
[1] Univ Bielefeld, Dept Econ & Business Adm, D-33501 Bielefeld, Germany
[2] Colorado State Univ, Dept Stat, Ft Collins, CO 80523 USA
来源：
BIOMETRIKA | 2011年 / 98卷 / 01期
关键词：
Knot selection; Maximum likelihood; Mixed model; Nonparametric regression;
D O I：
10.1093/biomet/asq081
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
A number of criteria exist to select the penalty in penalized spline regression, but the selection of the number of spline basis functions has received much less attention in the literature. We propose a likelihood-based criterion to select the number of basis functions in penalized spline regression. The criterion is easy to apply and we describe its theoretical and practical properties.
引用
收藏
页码：225 / 230
页数：6
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