Can you explain in what sense PCA is frequentist? I'm not sure it even deserves to be called a statistical method except insofar as it happens to be useful in statistics.
Yeah, calling PCA frequentist may be a bit of a stretch (although it's certainly not Bayesian). I think ICA (independent components analysis) could legitimately be called frequentist though, as it solves the blind source separation problem under certain independence assumptions (I don't know that much about either of these though, so I could be wrong).
Question in title.
This is obviously subjective, but I figure there ought to be some "go-to" paper. Maybe I've even seen it once, but can't find it now and I don't know if there's anything better.
Links to multiple papers with different focus would be welcome. For my current purpose I have a preference for one that aims low and isn't too long.