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ebdm: Implementation of Estimating Binary Dependency from Marginal Data

Provides a maximum likelihood estimation method to recover the joint distribution of two binary variables using only marginal summary data from multiple studies. This approach allows for privacy-preserving estimation in settings where individual-level data are unavailable. The method is fully described in the manuscript by Shang, Tsao and Zhang (2025) <doi:10.48550/arXiv.2505.03995>: "Estimating the Joint Distribution of Two Binary Variables from Their Marginal Summaries".

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: stats
Published: 2025-06-05
DOI: 10.32614/CRAN.package.ebdm
Author: Longwen Shang [aut, cre], Min Tsao [aut], Xuekui Zhang [aut]
Maintainer: Longwen Shang <shanglongwen0918 at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: ebdm results

Documentation:

Reference manual: ebdm.pdf

Downloads:

Package source: ebdm_1.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: ebdm_1.0.0.zip, r-oldrel: ebdm_1.0.0.zip
macOS binaries: r-release (arm64): ebdm_1.0.0.tgz, r-oldrel (arm64): ebdm_1.0.0.tgz, r-release (x86_64): ebdm_1.0.0.tgz, r-oldrel (x86_64): ebdm_1.0.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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