Canonical Correlation Analysis (CCA)

Canonical correlation analysis finds collections linear combinations of pairs of multivariate data vectors that are maximally correlated with each other, and uncorrelated with other pairs. Simultaneously observed data pairs can be analyzed to diagnose relationships between the pairs, and CCA on time-lagged pairs can be used for forecasting. MCA is a related method that maximizes covariance.