CorBin: Generate High-Dimensional Binary Data with Correlation Structures

We design algorithms with linear time complexity with respect to the dimension for three commonly studied correlation structures, including exchangeable, decaying-product and K-dependent correlation structures, and extend the algorithms to generate binary data of general non-negative correlation matrices with quadratic time complexity. Jiang, W., Song, S., Hou, L. and Zhao, H. "A set of efficient methods to generate high-dimensional binary data with specified correlation structures." The American Statistician. See <doi:10.1080/00031305.2020.1816213> for a detailed presentation of the method.

Version: 1.0.0
Published: 2020-11-14
DOI: 10.32614/CRAN.package.CorBin
Author: Wei Jiang [aut], Shuang Song [aut, cre], Lin Hou [aut] and Hongyu Zhao [aut]
Maintainer: Shuang Song <song-s19 at>
License: GPL-3
NeedsCompilation: no
CRAN checks: CorBin results


Reference manual: CorBin.pdf


Package source: CorBin_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): CorBin_1.0.0.tgz, r-oldrel (arm64): CorBin_1.0.0.tgz, r-release (x86_64): CorBin_1.0.0.tgz, r-oldrel (x86_64): CorBin_1.0.0.tgz
Old sources: CorBin archive


Please use the canonical form to link to this page.