[Mne_analysis] covariance with 'auto' option

[Elena Orekhova]

Hello,

I calculated noise covariance matrix on baseline using method=’auto’ to
find an optimal regularization:

cov = mne.compute_covariance(covepochs, method= ’auto’ , tmin=None,
tmax=None , verbose=True)



The optimal was ‘factor analysis’, but it gave me unacceptable solution.

When I look at whitening, it seems that ‘shrunk’ works better (see the
figures attached)!  What can be the problem?





 Elena
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20161018/404a633b/attachment-0001.html 
-------------- next part --------------
A non-text attachment was scrubbed...
Name: cov_factoranalysis.png
Type: image/png
Size: 89801 bytes
Desc: not available
Url : http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20161018/404a633b/attachment-0002.png 
-------------- next part --------------
A non-text attachment was scrubbed...
Name: cov_shrunk.png
Type: image/png
Size: 74563 bytes
Desc: not available
Url : http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20161018/404a633b/attachment-0003.png