Package: ebdm 3.0.1

ebdm: Estimating Bivariate Dependency from Marginal Data

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>.

Authors:Longwen Shang [aut], Min Tsao [aut], Xuekui Zhang [aut, cre, fnd]

ebdm_3.0.1.tar.gz
ebdm_3.0.1.zip(r-4.7-any)ebdm_3.0.1.zip(r-4.6-any)ebdm_3.0.1.zip(r-4.5-any)
ebdm_3.0.1.tgz(r-4.6-any)ebdm_3.0.1.tgz(r-4.5-any)
ebdm_3.0.1.tar.gz(r-4.7-any)ebdm_3.0.1.tar.gz(r-4.6-any)
ebdm_3.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
ebdm/json (API)

# Install 'ebdm' in R:
install.packages('ebdm', repos = c('https://ubcxzhang.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 2 scripts 215 downloads 3 exports 0 dependencies

Last updated from:bd2e04565e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK106
source / vignettesOK140
linux-release-x86_64OK109
macos-release-arm64OK100
macos-oldrel-arm64OK72
windows-develOK71
windows-releaseOK61
windows-oldrelOK55
wasm-releaseOK87

Exports:cor_bincor_contest_mixture

Dependencies: