CRand:

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    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.

   Since version 1.
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   Form:
   a = CRand( c )
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   ------
   Inputs
   ------
   c              Covariance matrix

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

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