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  "Title": "Generate a Random p x p Correlation Matrix",
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  "Author": "Daniel F. Schmidt [aut, cph, cre], Enes Makalic [aut, cph]",
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  "Description": "Implements the algorithm by Pourahmadi and Wang (2015)\n<doi:10.1016/j.spl.2015.06.015> for generating a random p x p\ncorrelation matrix. Briefly, the idea is to represent the\ncorrelation matrix using Cholesky factorization and p(p-1)/2\nhyperspherical coordinates (i.e., angles), sample the angles\nfrom a particular distribution and then convert to the standard\ncorrelation matrix form. The angles are sampled from a\ndistribution with pdf proportional to sin^k(theta) (0 < theta <\npi, k >= 1) using the efficient sampling algorithm described in\nEnes Makalic and Daniel F. Schmidt (2018) <arXiv:1809.05212>.",
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