Canonical Correlation & Principal Components Analysis

نویسنده

  • Aaron French
چکیده

Canonical Correlation is one of the most general of the multivariate techniques. It is used to investigate the overall correlation between two sets of variables (p’ and q’). The basic principle behind canonical correlation is determining how much variance in one set of variables is accounted for by the other set along one or more axes. If there is more than one axis, they must be orthogonal. Unlike many other techniques, there is no designation that one set of variables is independent and the other set dependent. Canonical correlation is a descriptive or exploratory technique rather than a hypothesis-testing procedure, and there are several ways data may be combined with this procedure.

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تاریخ انتشار 2002