Adding fweights and aweights to numpy.corrcoef
Hello, Would it be possible to add the fweights and aweights keyword arguments from np.cov to np.corrcoef? They would retain their meaning from np.cov as frequency- or importance-based weightings respectively. Yours, Corin Hoad
I seem to recall that there was a discussion on this and it was a lot trickier then expected. I think statsmodels might have options in this direction. - Sebastian On Thu, 2018-04-26 at 15:44 +0000, Corin Hoad wrote:
Hello,
Would it be possible to add the fweights and aweights keyword arguments from np.cov to np.corrcoef? They would retain their meaning from np.cov as frequency- or importance-based weightings respectively.
Yours, Corin Hoad _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
On Thu, Apr 26, 2018 at 11:59 AM, Sebastian Berg 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. I think statsmodels might have options in this direction. statsmodels still has only fweights (case weights) for covariance and
correlation
Josef - Sebastian On Thu, 2018-04-26 at 15:44 +0000, Corin Hoad wrote: Hello, Would it be possible to add the fweights and aweights keyword
arguments from np.cov to np.corrcoef? They would retain their meaning
from np.cov as frequency- or importance-based weightings
respectively. Yours,
Corin Hoad
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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
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.
Corin Hoad
On Fri, 27 Apr 2018 at 10:44 Corin Hoad
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
On Fri, May 11, 2018 at 7:43 AM, Corin Hoad
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
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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The discussed changes are implemented in PR #11078
Corin
On Fri, 11 May 2018 at 15:07
On Fri, May 11, 2018 at 7:43 AM, Corin Hoad
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
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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participants (3)
-
Corin Hoad
-
josef.pktd@gmail.com
-
Sebastian Berg