enough of the clutter. let’s get davis’ R-mode FA as quickly as possible. feel free to skip over this if you’re comfortable with it. we recall the design matrix X of centered data:

we compute :

x

=

we get its eigenstructure; we construct a diagonal matrix of the square roots of the eigenvalues:

we check that U is orthogonal:

x

=

we define (the factors) as the -weighted eigenvector matrix:

x

=

and we define (the scores) , “which project the n individual objects onto the principal vectors [factors].”

x

=

that was R-mode. Q-mode is similar. in fact, it’s more than similar, but we’ll get to that. the starting point is to form instead of .

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