A note on generating multivariate data with desired means, variances, and covariances
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A method is shown for creating a set of ɳ observations on Ƥ variables, with the p variables having specified means, variances, and covariances. This method differs from previous techniques in that it uses Crout factorization to develop the desired variance-covariance matrix instead of using the methods of component or factor analysis. Because the procedure assumes that it begins with Ƥ variables having zero means, unit variances, and zero intercorrelations, a procedure is also given for transforming the original data so that they fulfill these conditions
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