Functional Multiple-Set Canonical Correlation Analysis

被引：12

作者：

Hwang, Heungsun ^{[1
]}

Jung, Kwanghee

Takane, Yoshio

Woodward, Todd S. ^{[2
,3
]}

机构：

[1] McGill Univ, Dept Psychol, Montreal, PQ H3A 1B1, Canada

[2] Univ British Columbia, Vancouver, BC V5Z 1M9, Canada

[3] British Columbia Mental Hlth & Addict Res Inst, Vancouver, BC, Canada

来源：

PSYCHOMETRIKA | 2012年 / 77卷 / 01期

关键词：

functional data; multiple-set canonical correlation analysis; functional canonical correlation analysis; functional magnetic resonance imaging data; PRINCIPAL COMPONENT ANALYSIS; MUSICAL PERFORMANCE; FACTORIAL; DYNAMICS; CURVES; FUSION; FMRI;

D O I：

10.1007/s11336-011-9234-4

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the method solves a matrix eigen-analysis problem through the adoption of a basis expansion approach to approximating data and weight functions. We apply the proposed method to functional magnetic resonance imaging (fMRI) data to identify networks of neural activity that are commonly activated across subjects while carrying out a working memory task.

引用

页码：48 / 64

页数：17

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