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:
ebdm_3.0.1.tar.gz
ebdm_3.0.1.zip(r-4.7)ebdm_3.0.1.zip(r-4.6)ebdm_3.0.1.zip(r-4.5)
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✨
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')) |
- bin_example - Example Data: Binary Variables
- cont_example - Example Data: Continuous Variables
- mixture_example - Example Data: Mixture Model Summaries
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:bd2e04565e. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 106 | ||
| source / vignettes | OK | 130 | ||
| linux-release-x86_64 | OK | 101 | ||
| macos-release-arm64 | OK | 60 | ||
| macos-oldrel-arm64 | OK | 64 | ||
| windows-devel | OK | 72 | ||
| windows-release | OK | 72 | ||
| windows-oldrel | OK | 69 | ||
| wasm-release | OK | 86 |
Exports:cor_bincor_contest_mixture
Dependencies:
