[Scilab-users] spatial correlation coefficient: Is the MATLAB corrcoef function doing the job?
Heinz
heinznabielek at me.com
Thu Feb 8 22:38:35 CET 2018
From: users [mailto:users-bounces at lists.scilab.org] On Behalf Of Rafael
Guerra
Sent: 08 February 2018 18:55
To: Users mailing list for Scilab <users at lists.scilab.org>
Subject: Re: [Scilab-users] spatial correlation coefficient: Is the MATLAB
corrcoef function doing the job?
Hi Heinz,
Scilab computes the covariance matrix and from which the correlation matrix
can be obtained using formula in
https://en.wikipedia.org/wiki/Covariance_matrix
Check implementation below:
//START OF CODE
// https://en.wikipedia.org/wiki/Covariance_matrix
function Y=corrmatrix(M)
C = cov(M); // covariance matrix
D = sqrt(diag(C)); // standard deviations
D = inv(diag(D));
Y = D*C*D; // correlation matrix
endfunction
M = grand(9,3,"def")
M(:,2) = M(:,1)*2;
Y = corrmatrix(M);
disp(M,"M")
disp(Y,"Y")
// END OF CODE
For random generated xyz positions, I get the matrix below and this looks
fine with me:
1.000
-0.009
-0.003
-0.009
1.000
-0.001
-0.003
-0.001
1.000
But this here is a manufactured object and every singly xyz-value is
obtained from X-ray tomography
https://www.dropbox.com/s/87osn38agn8jfzo/Measured%2016867%20data%20points%2
0in%203d.png?dl=0
and looks much more regular than the Monte-Carlo. However, the correlation
analysis suggested here, gives much the same numbers.
1.000
-0.009
0.008
-0.009
1.000
-0.001
0.008
-0.001
1.000
Perhaps, I have asked the wrong question:
-->what I need is one single figures that summarizes the spatial
correlation.
Heinz
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