Hi, Dante-
Ooook, I think this can happen when the time series is not already demeaned before entering it into 3dNetCorr. If a residual time series is entered, which should have a mean of zero, then this large change would not happen. If you have a time series with a mean far away from zero, and then apply a weight that is zero in some places, that will look like a giant spike in the time series, which will drive high correlation. Thanks for pointing that out.
I could probably add another option, say "-weight_corr ..." to perform weighting of the Pearson correlation coefficient, such as described here:
[
en.wikipedia.org]
That might be more in line with your use case?
--pt
