CorBin
1.0.0Generate High-Dimensional Binary Data with Correlation Structures
Overview
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.
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- NOTE2026-03-109 OK · 5 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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- Return-value docs
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3 releases. Pick two to compare their code metrics. R releases are shown for context.
- archivedRemoved from CRAN2026-05-14email to the maintainer is undeliverable
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.0.02020-11-14 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 0.3.32019-10-19 · diff ↗
- 0.3.12019-08-08
- RR 3.6.0 released · 2019-04-26
Package metadata
- Total releases
- 3
- License
- GPL-3 OSI
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- 6.5 KB
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