On Estimating the Dimensionality in Canonical Correlation Analysis

In canonical correlation analysis the number of nonzero population correlation coefficients is called the dimensionality. Asymptotic distributions of the dimensionalities estimated by Mallows's criterion and Akaike's criterion are given for nonnormal multivariate populations with finite fourth moments. These distributions have a simple form in the case of elliptical populations, and modified criteria are proposed which adjust for nonzero kurtosis. An estimation method based on a marginal likelihood function for the dimensionality is introduced and the asymptotic distribution of the corresponding estimator is derived for multivariate normal populations. It is shown that this estimator is not consistent, but that a simple modification yields consistency. An overall comparison of the various estimation methods is conducted through simulation studies.