Multivariate Lognormal Simulation with Correlation
MVLOGNRAND MultiVariate Lognormal random numbers with correlation.
This function will generate multivariate lognormal random numbers with correlation.
Often one would simulation a lognormal distribution by first simulating a normal and then taking the exponent of it.
If you provide the correlation matrix to the multivariate normal random number generator and then exponeniate the results, you will not have the correlation stucture you input in the normal distribution because of the exponeniation. This function adjusts for that and passes the adjusted correlation matrix to the normal random number generator.
Example:
Mu = [ 11 12 13 ];
Sigma= [ .1 .3 .5 ];
Sims= 1e6;
CorrMat=[1 .2 .4 ; .2 1 .5 ; .4 .5 1];
y=MvLogNRand(Mu,Sigma,Sims,CorrMat );
corrcoef(y)
ans =
1 0.19927 0.40156
0.19927 1 0.50008
0.40156 0.50008 1
CorrMat =
1 0.2 0.4
0.2 1 0.5
0.4 0.5 1
Cite As
Stephen Lienhard (2024). Multivariate Lognormal Simulation with Correlation (https://www.mathworks.com/matlabcentral/fileexchange/6426-multivariate-lognormal-simulation-with-correlation), MATLAB Central File Exchange. Retrieved .
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- AI and Statistics > Statistics and Machine Learning Toolbox > Probability Distributions > Continuous Distributions > Lognormal Distribution >
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