Canonical Correlation and Multiple Correspondence Analyses

Kohei Adachi ()
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Kohei Adachi: Osaka University, Graduate School of Human Sciences

Chapter Chapter 14 in Matrix-Based Introduction to Multivariate Data Analysis, 2020, pp 211-228 from Springer

Abstract: Abstract In this chapter, we treat procedures for the data set in which variablesVariables are classified into some groups. Such a data set is expressed as a block matrixBlock matrix, introduced in Sect. 14.1. Then, we describe canonical correlation analysis (CCA)Canonical Correlation Analysis (CCA) for data with two groups of variablesVariables, which is followed by the introduction of generalized CCA (GCCA)Generalized Canonical Correlation Analysis (GCCA) for more than two groups of variablesVariables in Sect. 14.3.

Date: 2020
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DOI: 10.1007/978-981-15-4103-2_14

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