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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 mails.tsinghua.edu.cn> |
| 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: CorBin_1.0.0.zip, r-release: CorBin_1.0.0.zip, r-oldrel: CorBin_1.0.0.zip |
| 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 |
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