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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 |
| DOI: | 10.32614/CRAN.package.randcorr |
| 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 |
| Reference manual: | randcorr.pdf |
| Package source: | randcorr_1.0.tar.gz |
| Windows binaries: | r-devel: randcorr_1.0.zip, r-release: randcorr_1.0.zip, r-oldrel: randcorr_1.0.zip |
| macOS binaries: | r-release (arm64): randcorr_1.0.tgz, r-oldrel (arm64): randcorr_1.0.tgz, r-release (x86_64): randcorr_1.0.tgz, r-oldrel (x86_64): randcorr_1.0.tgz |
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