[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.29220/CSAM.2019.26.3.305

Higher-order solutions for generalized canonical correlation analysis

Kang, Hyuncheol (Division of Big Data and Management Engineering, Hoseo University)

Publication Information

Communications for Statistical Applications and Methods / v.26, no.3, 2019 , pp. 305-313 More about this Journal

Abstract

Generalized canonical correlation analysis (GCCA) extends the canonical correlation analysis (CCA) to the case of more than two sets of variables and there have been many studies on how two-set canonical solutions can be generalized. In this paper, we derive certain stationary equations which can lead the higher-order solutions of several GCCA methods and suggest a type of iterative procedure to obtain the canonical coefficients. In addition, with some numerical examples we present the methods for graphical display, which are useful to interpret the GCCA results obtained.

Keywords

generalized canonical correlation analysis; higher-order solutions; canonical weights; goodness of approximation indices; canonical loadings; explained variance indices;

Citations & Related Records

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