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Re: Simulating Correlated non-Normal Random Variables

• To: mathgroup at smc.vnet.net
• Subject: [mg32476] Re: Simulating Correlated non-Normal Random Variables
• From: Erich Neuwirth <erich.neuwirth at univie.ac.at>
• Date: Tue, 22 Jan 2002 03:20:09 -0500 (EST)
• References: <a2b4ge$lj2$1@smc.vnet.net>
• Sender: owner-wri-mathgroup at wolfram.com

you can apply the same method to any set of independent variables

when x1 ... x1 are independent variables
and A is a matrix

A.(x1,..xn)

has covariance matrix A'A

no normality assumptions are needed for that.





"Coleman, Mark" wrote:
> 
> Greetings,
> 
> This is not a Mathematica question per se, but I'm hoping members of this list
> might be able to point me in the right direction.
> 
> I'm constructing a Monte Carlo simulation procedure, where I need to
> draw a n-vector of correlated random variables, given that I know the
> univariate distribution of each element of the vector and the
> corresponding covariance matrix. This problem is straightforward for
> normally distributed random variables, where one can create N(0,1)
> variates and multiply by the matrix square root of the covariance matrix
> to created the correlated sample. I am dealing with non-normally
> distrubuted random variables, however. In my case they have the Beta
> distribution.
> 
> Can someone point me to a way to draw an n-vector of correlated beta
> random variables?
> 
> Thanks,
> 
> -Mark

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