[Numpy-discussion] Cross-covariance function

josef.pktd@gmai... josef.pktd@gmai...
Sat Jan 21 18:40:34 CST 2012


On Sat, Jan 21, 2012 at 6:26 PM, John Salvatier
<jsalvati@u.washington.edu> wrote:
> I ran into this a while ago and was confused why cov did not behave the way
> pierre suggested.

same here,
When I rewrote scipy.stats.spearmanr, I matched the numpy behavior for
two arrays, while R only returns the cross-correlation part.

Josef

>
> On Jan 21, 2012 12:48 PM, "Elliot Saba" <staticfloat@gmail.com> wrote:
>>
>> Thank you Sturla, that's exactly what I want.
>>
>> I'm sorry that I was not able to reply for so long, but Pierre's code is
>> similar to what I have already implemented, and I am in support of changing
>> the functionality of cov().  I am unaware of any arguments for a covariance
>> function that works in this way, except for the fact that the MATLAB cov()
>> function behaves in the same way. [1]
>>
>> MATLAB, however, has an xcov() function, which is similar to what we have
>> been discussing. [2]
>>
>> Unless you all wish to retain compatibility with MATLAB, I feel that the
>> behaviour of cov() suggested by Pierre is the most straightforward method,
>> and that if users wish to calculate the covariance of X concatenated with Y,
>> then they may simply concatenate the matrices explicitly before passing into
>> cov(), as this way the default method does not use 75% more CPU time.
>>
>> Again, if there is an argument for this functionality, I would love to
>> learn of it!
>> -E
>>
>> [1] http://www.mathworks.com/help//techdoc/ref/cov.html
>> [2] http://www.mathworks.com/help/toolbox/signal/ref/xcov.html
>>
>>
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