R help - Mar 2007 - generating lognormal variables with given correlation

Dear R users
 
I use simulated data to evaluate a model by sampling the parameters in
my model from lognormal distributions.
 
I would like these (lognormal distributed) parameters to be correlated,
that is, I would like to have pairwise samples of 2 parameters with a
given correlation coefficient.
 
I have seen that a covariance matrix can be fixed when generating random
variables from a multivariate normal distribution e.g. by the function
mvrnorm.
 
Is there a function to do the same for a multivariate lognormal
distribution?
 
Thank you!
 
Fabian

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Mollet, Fabian:
> I would like these (lognormal distributed) parameters to be correlated,
> that is, I would like to have pairwise samples of 2 parameters with a
> given correlation coefficient.
>  
> I have seen that a covariance matrix can be fixed when generating random
> variables from a multivariate normal distribution e.g. by the function
> mvrnorm.
>  
> Is there a function to do the same for a multivariate lognormal
> distribution?
I don't know about any, but you should be aware that not all values of the 
correlation is possible with lognormal distributions. For example, if both 
variables have a standard lognormal distribution, they can't have
correlation
less than 1/e = -0.37. As the variance of the two distributions increase, the 
absolute value of the maximum and minimum correlation possible decrease (to 
zero).

Using the normal product-moment correlation as a measure of dependence rarely 
makes much sense unless the association between the variables is linear.

-- 
Karl Ove Hufthammer