On Thu, Sep 26, 2013 at 6:42 PM, Nathaniel Smith wrote:
> On 26 Sep 2013 21:59, "Faraz Mirzaei" wrote:
>>
>> Thanks Josef and Nathaniel for your responses.
>>
>> In the application that I have, I don't use the correlation coefficient
>> matrix as a whole (so I don't care if it is PSD or not). I s
On 26 Sep 2013 21:59, "Faraz Mirzaei" wrote:
>
> Thanks Josef and Nathaniel for your responses.
>
> In the application that I have, I don't use the correlation coefficient
matrix as a whole (so I don't care if it is PSD or not). I simply read the
off-diagonal elements for pair-wise correlation coe
Thanks Josef and Nathaniel for your responses.
In the application that I have, I don't use the correlation coefficient
matrix as a whole (so I don't care if it is PSD or not). I simply read the
off-diagonal elements for pair-wise correlation coefficients. I use the
pairwise correlation coefficient
On 26 Sep 2013 17:32, wrote:
>
> On Thu, Sep 26, 2013 at 7:35 AM, Nathaniel Smith wrote:
> > By textbook I mean, users expect corrcoef to use this formula, which
> > is printed in every textbook:
> >
https://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient#For_a_sample
> > The
On Thu, Sep 26, 2013 at 7:35 AM, Nathaniel Smith wrote:
> On Thu, Sep 26, 2013 at 11:51 AM, wrote:
>> On Thu, Sep 26, 2013 at 4:21 AM, Nathaniel Smith wrote:
>>> If you want a proper self-consistent correlation/covariance matrix, then
>>> pairwise deletion just makes no sense period, I don't se
On Thu, Sep 26, 2013 at 11:51 AM, wrote:
> On Thu, Sep 26, 2013 at 4:21 AM, Nathaniel Smith wrote:
>> If you want a proper self-consistent correlation/covariance matrix, then
>> pairwise deletion just makes no sense period, I don't see how postprocessing
>> can help.
>
> clipping to [-1, 1] and
On Thu, Sep 26, 2013 at 6:51 AM, wrote:
> On Thu, Sep 26, 2013 at 4:21 AM, Nathaniel Smith wrote:
>> If you want a proper self-consistent correlation/covariance matrix, then
>> pairwise deletion just makes no sense period, I don't see how postprocessing
>> can help.
>
> clipping to [-1, 1] and f
On Thu, Sep 26, 2013 at 4:21 AM, Nathaniel Smith wrote:
> If you want a proper self-consistent correlation/covariance matrix, then
> pairwise deletion just makes no sense period, I don't see how postprocessing
> can help.
clipping to [-1, 1] and finding the nearest positive semi-definite matrix.
If you want a proper self-consistent correlation/covariance matrix, then
pairwise deletion just makes no sense period, I don't see how
postprocessing can help.
If you want a matrix of correlations, then pairwise deletion makes sense.
It's an interesting point that arguably the current ma.corrcoef
On Wed, Sep 25, 2013 at 11:05 PM, wrote:
> On Wed, Sep 25, 2013 at 8:26 PM, Faraz Mirzaei wrote:
>> Hi everyone,
>>
>> I'm using np.ma.corrcoef to compute the correlation coefficients among rows
>> of a masked matrix, where the masked elements are the missing data. I've
>> observed that in some
On Wed, Sep 25, 2013 at 8:26 PM, Faraz Mirzaei wrote:
> Hi everyone,
>
> I'm using np.ma.corrcoef to compute the correlation coefficients among rows
> of a masked matrix, where the masked elements are the missing data. I've
> observed that in some cases, the np.ma.corrcoef gives invalid coefficien
Hi everyone,
I'm using np.ma.corrcoef to compute the correlation coefficients among rows
of a masked matrix, where the masked elements are the missing data. I've
observed that in some cases, the np.ma.corrcoef gives invalid coefficients
that are greater than 1 or less than -1.
Here's an example:
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