Hi Tsjerk,
I really appreciate your comments. I proceeded as you recommended, and
calculate the subspace overlap in the way you proposed.
I first performed the analysis varying the starting points, instead of the
end ones. I start from 110 ns down to 0ns, with 10ns time intervals:
Normalized DT
Hi Miguel,
The fitting doesn't play a role; it's the dynamics of the system in the
internal frame. Because the internal frame moves, you fit, so that any
contribution due to the rigid body motion is removed.
For the rest you have to look at it like this: You start out somewhere and
walk (relax) t
Hi Tsjerk,
Thanks for the reply! So, let me see if I am getting the things right. The
same fitting structure is used for the overlap calculation. Since the
averaged structure is used for the covariance matrices, this is the reason
why the relaxation is included. Am I right?
The overall behavior of
Hi Miguel,
Sorry for not responding earlier, but the question isn't really simple :)
What you do is determining the covariance matrix from the start up to a
certain point and see for different end points what the overlap is with the
covariance matrix from the whole. This means that in all cases, t
Dear all,
I posted some days ago an issue regarding overlap values. If any of you is
experienced with this I would appreciate some comments. Please find below
the mentioned post:
I am doing PCA on a 110ns run.
When calculating the subspace overlap from independent PCA performed in
different time
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