Hi SH,

Thanks for your reply. I'm afraid I do require all those data points. I'm looking to compute the occupation density (local time) of a fractional OU sheet, which is a pain because it amounts to a sort of `two scale' system where the fractal structure of the fOU sheet needs to be present at a scale much smaller than the resolution of the local time process. The long-range correlation property of the fBm means I can't really do it in sections.

Your suggestion is much appreciated however :)

John

Hi John

I don't know the answers to your questions, I'm just wondering, do you really have ~10^11 datapoints, and you want to know the spectrum also with 10^11 datapoints?? Sounds like an absurd high precision to know a spectrum. Can you divide the data in (say) pieces of 10^6 point, calculate the fft for each, and average them? This will give you a spectrum with 10^6 datapoints, which is generally more than enough to get typical frequencies and features out. This is a procedure I've done many times on multi-GB datasets works very well.

--SH