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Re: Re: Simulating Correlated non-Normal Random Variables

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  • Subject: [mg32594] Re: [mg32476] Re: Simulating Correlated non-Normal Random Variables
  • From: "Johannes Ludsteck" <johannes.ludsteck at>
  • Date: Thu, 31 Jan 2002 01:45:16 -0500 (EST)
  • Organization: Universitaet Regensburg
  • Sender: owner-wri-mathgroup at

Erich Neuwirth wrote:

>>you can apply the same method to any set of independent variables
>>when x1 ... x1 are independent variables
>>and A is a matrix
>>has covariance matrix A'A
>>no normality assumptions are needed for that.

The statement concerning the covariance Matrix ist correct,
but it is not clear in general,
whether you obtain a multivariate beta-distribution
if you apply this transformation to a vector of univariate
beta-distributed random variables.
The invariance property (linear combinations of normal deviates
are again normal) is a special property of normal deviates.
If this is not clear to you, please try adding two uniform
deviates with different support.

Best regards,

Johannes Ludsteck
Institut fuer Volkswirtschaftslehre
Lehrstuhl Prof. Dr. Moeller
Universitaet Regensburg
Universitaetsstrasse 31
93053 Regensburg
Tel +49/0941/943-2741

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