On Fri, Jun 15, 2012 at 4:50 PM, Yaroslav Halchenko wrote:
>
> On Fri, 15 Jun 2012, [email protected] wrote:
>> https://github.com/PyMVPA/PyMVPA/blob/master/mvpa2/misc/dcov.py#L160
>> looks like a double sum, but wikipedia only has one sum, elementwise product.
>
> sorry -- I might be slow -- w
On Fri, 15 Jun 2012, [email protected] wrote:
> https://github.com/PyMVPA/PyMVPA/blob/master/mvpa2/misc/dcov.py#L160
> looks like a double sum, but wikipedia only has one sum, elementwise product.
sorry -- I might be slow -- what sum? there is only an outer product in
160:Axy = Ax[:, None
On Fri, Jun 15, 2012 at 4:20 PM, Yaroslav Halchenko wrote:
> Here is a comparison to output of my code (marked with >):
>
> 0.00458652660079 0.788017364828 0.00700027844478 0.00483928213727
>> 0.145564526722 0.480124905375 0.422482399359 0.217567496918
> 6.50616752373e-07 7.99461373461e-05 0.0070
Here is a comparison to output of my code (marked with >):
0.00458652660079 0.788017364828 0.00700027844478 0.00483928213727
> 0.145564526722 0.480124905375 0.422482399359 0.217567496918
6.50616752373e-07 7.99461373461e-05 0.00700027844478 0.0094610687282
> 0.120884106118 0.249205123601 0.4224823
On Fri, Jun 15, 2012 at 3:50 PM, wrote:
> On Fri, Jun 15, 2012 at 10:45 AM, Yaroslav Halchenko
> wrote:
>>
>> On Fri, 15 Jun 2012, Satrajit Ghosh wrote:
>>> hi yarik,
>>> here is my attempt:
>>>
>>> [1]https://github.com/satra/scikit-learn/blob/enh/covariance/sklearn/covariance/distan
On Fri, Jun 15, 2012 at 10:45 AM, Yaroslav Halchenko
wrote:
>
> On Fri, 15 Jun 2012, Satrajit Ghosh wrote:
>> hi yarik,
>> here is my attempt:
>>
>> [1]https://github.com/satra/scikit-learn/blob/enh/covariance/sklearn/covariance/distance_covariance.py
>> i'll look at your code in det
On Fri, 15 Jun 2012, Satrajit Ghosh wrote:
>hi yarik,
>here is my attempt:
>
> [1]https://github.com/satra/scikit-learn/blob/enh/covariance/sklearn/covariance/distance_covariance.py
>i'll look at your code in detail later today to understand the uv=True
it is just to compute dCo[v
hi yarik,
here is my attempt:
https://github.com/satra/scikit-learn/blob/enh/covariance/sklearn/covariance/distance_covariance.py
i'll look at your code in detail later today to understand the uv=True case.
cheers,
satra
On Fri, Jun 15, 2012 at 10:19 AM, Yaroslav Halchenko wrote:
> I haven't
I haven't had a chance to play with it extensively but I have a basic
implementation:
https://github.com/PyMVPA/PyMVPA/blob/master/mvpa2/misc/dcov.py
which still lacks statistical assessment, but provides dCov, dCor values
and yes -- it is "inherently multivariate", but since also could be
useful
hi yarik,
hm... interesting -- and there is no comparison against "minimizing
> independence"? e.g. dCov measure
> http://en.wikipedia.org/wiki/Distance_correlation which is really simple
> to estimate and as intuitive as a correlation coefficient
>
thanks for bringing up dCov. have you had a cha
Submitted 5/07; Revised 6/11; Published 5/12
It takes such a long time ...
On Fri, Jun 15, 2012 at 8:58 PM, Satrajit Ghosh wrote:
> fyi
>
> -- Forwarded message --
> From: joshua vogelstein
> Date: Fri, Jun 15, 2012 at 12:35 AM
>
> http://jmlr.csail.mit.edu/papers/volume13/song
hm... interesting -- and there is no comparison against "minimizing
independence"? e.g. dCov measure
http://en.wikipedia.org/wiki/Distance_correlation which is really simple
to estimate and as intuitive as a correlation coefficient
On Fri, 15 Jun 2012, Satrajit Ghosh wrote:
>fyi
>
fyi
-- Forwarded message --
From: joshua vogelstein
Date: Fri, Jun 15, 2012 at 12:35 AM
http://jmlr.csail.mit.edu/papers/volume13/song12a/song12a.pdf
these guys define a nice nonlinear/nonparametric measure of correlation
that might be of interest to you.
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