Analyzing EEG / MEG data with PyMC3

Hi

yes that is very clear now.

  1. Yes, by scale parameter I meant the std, might be quite challenging to sample from an uniform prior in the range 0.001 - 1000.

  2. I only played around with it a couple of times, but I believe you could use a Multivariate Normal with your noise matrix as covariance matrix. The lecture by Richard McElreath on Gaussian Processes is the most accessible resource I found so far on the subject.

  3. The same logic I suspect it also applies to samples, since they represent different points in time you might expect some form of temporal structure to be present. This would probably require a spatio-temporal model but this is something way out of my depth.

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