OK, the idea is that instead of using real proxies we'll use random data. This has the advantage that we can make as many series as we like. It has the disadvantage that the data may not look like the real series.
Anyway: I ran the above stuff 4 times over, to generate 4 realisations. If I were a stats whizz then I'd just prove the properties of the output, but its easier to just run examples. Here are the 4 (click to see):
But... when we look at the associated eigenvalues, there is a problem (JA finds the same, and in fact found it first). When I do the MBH method on true proxy data, eigenvalue 1 is 0.55 (1000-) or 0.38 (1400-), and clearly larger than following values. When I do it on random data, eigenvalue 1 is 0.03 or thereabouts, and indistinct from following values. I think that is important.
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