[SciPy-User] [SciPy-user] Covariance matrix

josef.pktd@gmai... josef.pktd@gmai...
Mon Feb 13 09:40:12 CST 2012


On Mon, Feb 13, 2012 at 10:30 AM, Johannes Eckstein <eckjoh2@web.de> wrote:
> Haha, Thanks Pauli
>
> maybe good, that I don't have that much memory.
> I just realized that I was confused by the indices...
> I had it the way round, before... another question:
>
> M = X.H * X
>
> with X being a de-trended process does give the (unscaled) covariance
> matrix?

for linear least squares the unscaled covariance matrix is the inverse
of dot(X.T, X)

for nonlinear least squares X is replaced by the Jacobian.

Josef

>
> cheers, Johannes
>> 13.02.2012 09:59, Johannes Eckstein kirjoitti:
>> [clip]
>>> how can I do a matrix multiplication of a matrix X with shape: (240001, 4)
>>>
>>> M = X * X.H
>>>
>>> when I do this I get the following:
>>>      return N.dot(self, asmatrix(other))
>>> ValueError: array is too big.
>>>
>>> What is the best way to avoid this error?
>> The result would be a 240001 x 240001 matrix that consumes 430 GB of
>> memory. Do you really have that much available?
>>
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