Summary
A method is introduced by imposing linear constraints upon parameters corresponding to more than two sets of variables. We call the method introduced here ‘generalized canonical correlation analysis with linear constraint’. It covers canonical correlation analysis with linear constraints proposed by Yanai & Takane (1992) as its special case. Further, by employing dummy variables, our method turns out to be identical to the multiple correspondence analysis with linear constraints.
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References
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© 1998 Springer Japan
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Yanai, H. (1998). Generalized Canonical Correlation Analysis with Linear Constraints. In: Hayashi, C., Yajima, K., Bock, HH., Ohsumi, N., Tanaka, Y., Baba, Y. (eds) Data Science, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Tokyo. https://doi.org/10.1007/978-4-431-65950-1_59
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DOI: https://doi.org/10.1007/978-4-431-65950-1_59
Publisher Name: Springer, Tokyo
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