Mercurial > hg > ltpda
comparison m-toolbox/classes/+utils/@math/corr2cov.m @ 0:f0afece42f48
Import.
| author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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| date | Wed, 23 Nov 2011 19:22:13 +0100 |
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| -1:000000000000 | 0:f0afece42f48 |
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| 1 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | |
| 2 % CORR2COV | |
| 3 % Convert correlartion matrix to covariance matrix | |
| 4 % | |
| 5 % SigC Vector of length n with the standard deviations of each process. n | |
| 6 % is the number of random processes. | |
| 7 % | |
| 8 % CorrC n-by-n correlation coefficient matrix. If ExpCorrC is not | |
| 9 % specified, the processes are assumed to be uncorrelated, and the identity | |
| 10 % matrix is used. | |
| 11 % | |
| 12 % Algorithm | |
| 13 % | |
| 14 % Covar(i,j) = CorrC(i,j)*(SigmC(i)*SigmC(j) | |
| 15 % | |
| 16 % L Ferraioli 10-10-2010 | |
| 17 % | |
| 18 % $Id: corr2cov.m,v 1.1 2010/11/16 16:41:37 luigi Exp $ | |
| 19 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | |
| 20 | |
| 21 | |
| 22 function Covar = corr2cov(CorrC,SigC) | |
| 23 | |
| 24 Covar = CorrC; | |
| 25 | |
| 26 for tt=1:size(CorrC,1) | |
| 27 for hh=1:size(CorrC,2) | |
| 28 Covar(tt,hh) = CorrC(tt,hh)*SigC(tt)*SigC(hh); | |
| 29 end | |
| 30 end | |
| 31 end |