CRand:

Path: Math/Probability

% Covariance matrix transformation
 Given a covariance matrix, c, finds a transformation matrix that transforms a
 vector of normal random numbers each with a standard deviation of 1 into a
 vector modeled by the covariance matrix. If x is the vector of normal random
 numbers

    y = ax

 such that

    E(xx') = I

 then y is a vector of random numbers such that

    E(yy') = c

 Uses the Cholesky decomposition of c. c must be positive
 definite.

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   Form:
   a = CRand( c )
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   ------
   Inputs
   ------
   c              Covariance matrix

   -------
   Outputs
   -------
   a              Transformation matrix

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