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Canonical Correlation and Multiple Correspondence Analyses

In: Matrix-Based Introduction to Multivariate Data Analysis

Author

Listed:
  • Kohei Adachi

    (Osaka University, Graduate School of Human Sciences)

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.

Suggested Citation

  • Kohei Adachi, 2020. "Canonical Correlation and Multiple Correspondence Analyses," Springer Books, in: Matrix-Based Introduction to Multivariate Data Analysis, edition 2, chapter 0, pages 211-228, Springer.
    • Handle: RePEc:spr:sprchp:978-981-15-4103-2_14
    DOI: 10.1007/978-981-15-4103-2_14
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