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A procedure for generating multivariate nonnormal distributions is proposed. Our procedure gener-ates average values of intercorrelations much closer to population parameters thancompeting procedures for skewed and/or heavy tailed distributions and for small sample sizes. Also, it eliminates the necessity of conducting a factorization procedure on the population correlation matrix that underlies the random devi-ates, and it is simpler to code in a programming language (e.g,, FORTRAN). Numerical examples demon-strating the procedures are given. Monte Carlo results indicate our procedure yields excellent agreement between population parameters and average values of intercorrelation, skew, andkurtosis.
Headrick et al. (1999) studied this question.