I have some set of measurements that I have represented as vectors $x^t$ for $t \in \{ 1, 2, ...\}$.
I want to test "convergence" of the process (visually) in some sense.
I thought maybe I could run PCA on $x^t$ and then plot the projections to the first principal component, 2nd, etc... and see whether these plots converge to something.
What is the right way to do it? There is variance in between samples, of course, so just plotting the first PCA component will not necessarily converge to something. But what should I look for, and how can I make it visually compelling? (Or maybe there is another, better way of testing the "convergence" of these $x^t$?)
(Please note: the $x^t$ are not coming from an MCMC process, but maybe tools from there could be used?)