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:: Volume 17, Issue 2 (3-2013) ::
Andishe 2013, 17(2): 81-91 Back to browse issues page
Generalization of Canonical Correlation Analysis from Multivariate to Functional Cases and its related problems
Abstract:   (7141 Views)
In multivariate cases, the aim of canonical correlation analysis (CCA) for two sets of variables x and y is to obtain linear combinations of them so that they have the largest possible correlation. However, when x and y are continouse functions of another variable (generally time) in nature, these two functions belong to function spaces which are of infinite dimension, and CCA for them should be carried out by using some tools provided by functional data analysis. In this paper we first review definitions and concepts of CCA for multivariate data, and then express those of CCA for functional data with considering the problems occur when generalizing the concepts from multivariate to functional cases. We have also treated a real functional data set and interpreted the obtained results.
Keywords: Function Data Analysis, Multivariate Canonical Correlation Analysis, Functional canonical correlation analysis
Full-Text [PDF 3303 kb]   (4013 Downloads)    
Type of Study: Applicable | Subject: General
Received: 2012/12/4 | Accepted: 2013/07/29 | Published: 2014/07/12
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Generalization of Canonical Correlation Analysis from Multivariate to Functional Cases and its related problems. Andishe 2013; 17 (2) :81-91
URL: http://andisheyeamari.irstat.ir/article-1-204-en.html


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Volume 17, Issue 2 (3-2013) Back to browse issues page
مجله اندیشه آماری Andishe _ye Amari
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