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2016•Unpublished venueOpen access

Canonical Correlation and Multiple Correspondence Analyses

Kohei Adachi

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Abstract

In this chapter, we treat procedures for the data set in which variables are classified into some groups. Such a data set is expressed as a block matrix Block matrix , introduced in Sect. 14.1. Then, we describe canonical correlation analysis (CCA)Canonical correlation analysis (CCA) for data with two groups of variables, which is followed by the introduction of generalized CCA (GCCA) for more than two groups of variables in Sect. 14.3. GCCA provides a foundation for a procedure analyzing the multivariate categorical data Multivariate categorical data described in Sect. 14.4.

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What this paper is about

In this chapter, we treat procedures for the data set in which variables are classified into some groups. Such a data set is expressed as a block matrix Block matrix , introduced in Sect. 14.1. Then, we describe canonical correlation analysis (CCA)Canonical correlation analysis (CCA) for data with two groups of variables, which is followed by the introduction of generalized CCA (GCCA) for more than two groups of variables in Sect. 14.3. GCCA provides a foundation for a procedure analyzing the multivariate categorical data Multivariate categorical data described in Sect. 14.4.

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Available abstract

In this chapter, we treat procedures for the data set in which variables are classified into some groups. Such a data set is expressed as a block matrix Block matrix , introduced in Sect. 14.1. Then, we describe canonical correlation analysis (CCA)Canonical correlation analysis (CCA) for data with two groups of variables, which is followed by the introduction of generalized CCA (GCCA) for more than two groups of variables in Sect. 14.3. GCCA provides a foundation for a procedure analyzing the multivariate categorical data Multivariate categorical data described in Sect. 14.4.

Key concepts: Categorical variable, Canonical correlation, Canonical analysis, Multivariate statistics, Mathematics, Data Matrix, Correlation, Correspondence analysis

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