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 259 downloads 3 exports 0 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK112
source / vignettesOK134
linux-releaseOK109
macos-releaseOK71
macos-oldrelOK75
windows-develOK51
windows-releaseOK59
windows-oldrelOK60
wasm-releaseOK102

Exports:cor_bincor_contest_mixture

Dependencies: