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


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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