On Fri, May 11, 2018 at 7:43 AM, Corin Hoad <corinhoad@gmail.com> wrote:
Are there any further thoughts on this? If it's simply allowing corrcoef to hand off the keyword arguments to cov I can make a simple PR with the change.

No further thoughts from my side. I don't see a problem.

Aside: And the degrees of freedom correction, which was one of the ambiguous issues in the cov case, will not matter in the corrcoef case because it cancels in the latter.

Josef

 


Corin Hoad

On Fri, 27 Apr 2018 at 10:44 Corin Hoad <corinhoad@gmail.com> wrote:
I seem to recall that there was a discussion on this and it was a lot
trickier then expected.

But given that numpy has the weights already for cov, then I don't see any additional issues
whith adding it also to corrcoef.
 
corrcoef is just rescaling the cov, so there is nothing special to add except that corrcoef hands off the options to cov.

This was my understanding. I am currently just using my own copy of corrcoef which forwards the aweights and fweights arguments directly to np.cov. Is this the correct approach?

Corin Hoad

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