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An asymptotic behavior of canonical correlation analysis is studied whendimension d grows and the sample size n is fxed. In particular, we areinterested in the conditions for which CCA works or fails in the HDLSSsituation. This technical report investigates those conditions in a rathersimplified setting where there exists one pair of directions in two sets ofrandom variables with non-zero correlation between two sets of scores on them.Proofs and an extensive simulation study supports the findings.

High-Dimension, Low Sample Size Asymptotics of Canonical Correlation Analysis