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Re: Covariance Matrix [message #92000 is a reply to message #86847] Mon, 28 September 2015 11:26 Go to previous message
andrei.makeev is currently offline  andrei.makeev
Messages: 1
Registered: September 2015
Junior Member
Amin,

from your code excerpt, it looks like the way you define the
mean (expected value) of the random vector for computing
covariance is incorrect.
It is not the mean of vector's elements, but each element of
the vector is the mean of the random variable. I.e. for each
entry in the vector, you'd have to provide the corresponding
sample mean, like for element a1 it'd <a1>, for element a2,
<a2>, etc. Vector A itself, is not sufficient for calculating its
covariance, you need to have a corresponding vector of means
for each element of it.

Andrei.


On Saturday, December 7, 2013 at 7:11:41 AM UTC-5, Amin Farhang wrote:
> Dear All,
>
> I have N observed data as a vector, and I need to compute its NxN covariance matrix, but IDL correlate function just return one value as the correlation (or covariance) between two vectors and do not return a matrix.
> So how can I compute NxN covariance matrix of below vector (for example):
>
> IDL> A = [1,2,3,4,5]
>
>
> Thanks in advance,
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