ContextLab / ContextLab/supereeg
distance metrics for averaging correlation matrices
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- Dominant language
- Python
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Description
Our current implementation computed subject-wise correlation matrices, fisher's r2zs them, computes the euclidean mean and then inverts the fisher's r2z (i.e. z2r)
We could explore other distance functions such as log-euclidean and riemannian. The logic being that SPD matrices live on a curved manifold, so euclidean averaging might be sub-optimal.
This figure gives a good intuition for why a non-euclidean distance metric might be better:
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