From: users [mailto:users-boun...@lists.scilab.org] On Behalf Of Rafael Guerra Sent: 08 February 2018 18:55 To: Users mailing list for Scilab <users@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
_______________________________________________ users mailing list users@lists.scilab.org http://lists.scilab.org/mailman/listinfo/users
