randcorr: Generate a Random p x p Correlation Matrix
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) <doi:10.48550/arXiv.1809.05212>.
Version: |
1.0 |
Published: |
2018-11-16 |
Author: |
Daniel F. Schmidt [aut, cph, cre],
Enes Makalic [aut, cph] |
Maintainer: |
Daniel F. Schmidt <daniel.schmidt at monash.edu> |
License: |
GPL (≥ 3) |
NeedsCompilation: |
no |
Citation: |
randcorr citation info |
CRAN checks: |
randcorr results |
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