Abstract
We describe how many dimension reduction strategies are connected conceptually and philosophically, paving the way for a unified approach to multivariate dimension reduction in statistics. Specific methods covered include envelopes, sufficient dimension reduction methods like SIR and SAVE, principal components, principal fitted components, and partial least squares.
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