Quote:
Originally Posted by Oblarg
This appears to be correct, with one minor quibble: why not just write M = AO where the elements of O are random variables with the appropriate variance? It doesn't really make it cleaner to split it into a zero-mean "noise variable" plus a flat mean.
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That would be different, I think. N is match noise and an m x 1 vector. If I understand your equation correctly, O would be the OPR random variable with mean of the "actual" OPR and some variance, but O is t x 1 and not m x 1, so I don't think they're the same. And the noise that the regression is computing is truly the noise to be expected in each match outcome, not the noise in the OPR estimates themselves. Or am I misunderstanding what you're saying?