High-Performance Open-Source Archive
Provides statistical methods for estimating bivariate dependency (correlation) from marginal summary statistics across multiple studies. The package supports three modules of bivariate joint distribution estimated from marginal summary data: (1) two binary, (2) two continuous, (3) one binary and one continuous These methods enable privacy-preserving joint estimation when individual-level data are unavailable. The approaches are detailed in Shang, Tsao, and Zhang (2025a) <doi:10.48550/arXiv.2505.03995> and Shang, Tsao, and Zhang (2025b) <doi:10.48550/arXiv.2508.02057>.
| Version: | 3.0.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats |
| Published: | 2026-04-23 |
| DOI: | 10.32614/CRAN.package.ebdm |
| Author: | Longwen Shang [aut], Min Tsao [aut], Xuekui Zhang [aut, cre, fnd] |
| Maintainer: | Xuekui Zhang <ubcxzhang at gmail.com> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | no |
| CRAN checks: | ebdm results |
| Reference manual: | ebdm.html , ebdm.pdf |
| Package source: | ebdm_3.0.1.tar.gz |
| Windows binaries: | r-devel: ebdm_3.0.1.zip, r-release: ebdm_3.0.1.zip, r-oldrel: ebdm_3.0.1.zip |
| macOS binaries: | r-release (arm64): ebdm_3.0.1.tgz, r-oldrel (arm64): ebdm_3.0.1.tgz, r-release (x86_64): ebdm_3.0.1.tgz, r-oldrel (x86_64): ebdm_3.0.1.tgz |
| Old sources: | ebdm archive |
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