Global optimization of the generalized cross-validation criterion

被引：24

作者：

Kent, JT

Mohammadzadeh, M

机构：

[1] Univ Leeds, Dept Stat, Leeds LS2 9JT, W Yorkshire, England

[2] Tarbiat Modares Univ, Dept Stat, Tehran, Iran

来源：

STATISTICS AND COMPUTING | 2000年 / 10卷 / 03期

关键词：

regularization; smoothing splines; smoothing parameter; generalized cross-validation; interval analysis;

D O I：

10.1023/A:1008939510946

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Generalized cross-validation is a method for choosing the smoothing parameter in smoothing splines and related regularization problems. This method requires the global minimization of the generalized cross-validation function. In this paper an algorithm based on interval analysis is presented to find the globally optimal value for the smoothing parameter, and a numerical example illustrates the performance of the algorithm.

引用

页码：231 / 236

页数：6

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