Model selection using modified AIC and BIC in joint modeling of paired functional data

被引：9

作者：

Wei, Jiawei ^{[1
]}

Zhou, Lan ^{[1
]}

机构：

[1] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA

来源：

STATISTICS & PROBABILITY LETTERS | 2010年 / 80卷 / 23-24期

基金：

美国国家科学基金会;

关键词：

AIC; SIC; Functional principle components; Penalized splines; Mixed effects model; CROSS-VALIDATION;

D O I：

10.1016/j.spl.2010.08.020

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：

A modified version of the Akaike information criterion and two modified versions of the Bayesian information criterion are proposed to select the number of principal components and to choose the penalty parameters of penalized splines in a joint model of paired functional data. Numerical results show that, compared with an existing procedure using the cross-validation, the procedure based on the information criteria is computationally much faster while giving a similar performance. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：1918 / 1924

页数：7

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