The discussed changes are implemented in PR #11078
Corin
On Fri, 11 May 2018 at 15:07 wrote:
> 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 wit
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
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 wrote:
> I seem to recall that there was a discussion on this and it was a lot
>>> trickie
>
> 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
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
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 +, Corin Hoad wrote:
> Hello,
>
> Would it be possible to add the fweights and aweights keyword
> a
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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