Theoretical Mathematics & Applications

A Predictive Model for Canonical Correlation Analysis with Implications for the Simple and Multiple Correlations

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•                                                    Abstract
  
  

  This study presents a new formulation for canonical correlation analysis as an equivalent multiple regression model for two Gaussian random vectors. In addition, implications for the simple and multiple correlations are discussed. The new model can also be extended to measure nonlinear associations between sets of variables.