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Three-Way Principal Component Analysis

In: Matrix-Based Introduction to Multivariate Data Analysis

Author

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  • Kohei Adachi

    (Osaka University, Graduate School of Human Sciences)

Abstract

In Chap. 5 , principalThree-Way Principal Component Analysis (3WPCA) component analysisPrincipal Component Analysis (PCA) (PCA) was introduced as the reduced rank approximationReduced rank approximation of a data matrix. This matrix should be noted to be a two-way array of rows × columnsColumn. We often encounter three-way data arraysThree-way data array, however, an example of which is a set of scores of examinees for multiple tests administered on different occasions. These scores form a three-way array of examinees × tests × occasions. Modified PCAPrincipal Component Analysis (PCA) procedures specified for similar three-way data are known as three-way PCA (3WPCAThree-Way Principal Component Analysis (3WPCA)). Popular 3WPCA procedures are introduced in this chapter.

Suggested Citation

  • Kohei Adachi, 2020. "Three-Way Principal Component Analysis," Springer Books, in: Matrix-Based Introduction to Multivariate Data Analysis, edition 2, chapter 0, pages 311-339, Springer.
    • Handle: RePEc:spr:sprchp:978-981-15-4103-2_20
    DOI: 10.1007/978-981-15-4103-2_20
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