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I am aware that given the covariance matrix, we can generate correlated random variables by Cholesky Decomposition or SVD. (viz. How to generate correlated random numbers (given means, variances and degree of correlation)?) I am interested to know if we could extend this idea to generate correlated random variables using higher comoments, such as the symmetric cokurtosis?

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