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Re: Computing a covariance matrix

• To: mathgroup at smc.vnet.net
• Subject: [mg73653] Re: Computing a covariance matrix
• From: Paul Abbott <paul at physics.uwa.edu.au>
• Date: Sat, 24 Feb 2007 02:08:30 -0500 (EST)
• Organization: The University of Western Australia
• References: <erme5t$i8b$1@smc.vnet.net>

In article <erme5t$i8b$1 at smc.vnet.net>,
 eleutheroskaiwraios at googlemail.com wrote:

> I was looking on how to compute a covariance matrix given a set of
> measurements and I was utterly frustrated having to jump from one
> discussion group to another and harvesting the web through maths
> websites having to cope with all sorts of notations. 

I would have thought that you would find the required 
derivation/computation in _many_ places.

> I managed to find a nice example on how to derive a covariance matrix and decided to
> share it with you :)
> 
> Go to:
> 
> 
> "How the stat packages compute a correlation matrix"
> 
> http://luna.cas.usf.edu/~mbrannic/files/pmet/vcv2.htm
>  
> It should be quite easy to understand how it is done. It even shows
> you how to standardise the matrix at the end.
>
> NOTE: this is cross-posted at:
> 
> sci.math
> sci.stat.math
> comp.soft-sys.math.mathematica
> alt.math.undergrad

As far as I can see, you have only posted this message to MathGroup 
(comp.soft-sys.math.mathematica), not to the other groups.

Also, I'm not sure what this has to do with Mathematica specificially? I 
note that CovarianceMatrix, which computes VCV in your notation, is in 
the package

  << Statistics`MultiDescriptiveStatistics`

Here is a direct Mathematica implementation of your example:

 X = {{1, 2, 3}, {2, 3, 4}, {1, 2, 3}, {5, 4, 3}, {4, 4, 4}}

 x = Transpose[X] - Mean[X]

 SSCP = x . Transpose[x]

 VCV = SSCP/(Length[X] - 1)

 s = Sqrt[Variance /@ x]

 correlationmatrix = VCV/Outer[Times, s, s]

Cheers,
Paul

_______________________________________________________________________
Paul Abbott                                      Phone:  61 8 6488 2734
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