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.

1.30 score 2 scripts 336 downloads 3 exports 0 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK88
source / vignettesOK156
linux-releaseOK83
macos-releaseOK84
macos-oldrelOK91
windows-develOK70
windows-releaseOK49
windows-oldrelOK56
wasm-releaseOK67

Exports:cor_bincor_contest_mixture

Dependencies: