On knot placement for penalized spline regression

被引:7
|
作者
Yao, Fang [2 ]
Lee, Thomas C. M. [1 ,3 ]
机构
[1] Chinese Univ Hong Kong, Dept Stat, Shatin, Hong Kong, Peoples R China
[2] Univ Toronto, Dept Stat, Toronto, ON M5S 3G3, Canada
[3] Colorado State Univ, Dept Stat, Ft Collins, CO 80523 USA
基金
美国国家科学基金会;
关键词
knot placement; local extrema; nonparametric regression; penalized splines; semiparametric regression;
D O I
10.1016/j.jkss.2008.01.003
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper Studies the problem of knot placement in penalized regression spline fitting. Given a pre-specified number of knots, most existing knot placement methods allocate the knots in an equally spaced fashion. This paper proposes a simple knot placement scheme for improving such "equally spaced methods". This new scheme first identifies locations of local extrema in the target function, and then it places additional knots ill Such places. The rationale behind this is that quite often such local extrema coincide with the critical locations for placing knots. The proposed scheme is shown to be superior in a Simulation study. (c) 2008 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:259 / 267
页数:9
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