Implements the algorithm by Pourahmadi and Wang (2015) <doi:10.1016/j.spl.2015.06.015> for generating a random p x p correlation matrix. Briefly, the idea is to represent the correlation matrix using Cholesky factorization and p(p-1)/2 hyperspherical coordinates (i.e., angles), sample the angles from a particular distribution and then convert to the standard correlation matrix form. The angles are sampled from a distribution with pdf proportional to sin^k(theta) (0 < theta < pi, k >= 1) using the efficient sampling algorithm described in Enes Makalic and Daniel F. Schmidt (2018) <arXiv:1809.05212>.
|Author||Daniel F. Schmidt [aut, cph, cre], Enes Makalic [aut, cph]|
|Maintainer||Daniel F. Schmidt <firstname.lastname@example.org>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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