Package: ebdm
Type: Package
Title: Estimating Bivariate Dependency from Marginal Data
Version: 3.0.0
Authors@R: 
    c(
      person(given = "Longwen", family = "Shang", role = c("aut", "cre"), email = "shanglongwen0918@gmail.com"),
      person(given = "Min", family = "Tsao", role = "aut"),
      person(given = "Xuekui", family = "Zhang", role = "aut")
    )
Description: Provides statistical methods for estimating bivariate dependency (correlation) from marginal summary statistics across multiple studies. 
    The package supports three modules: (1) bivariate correlation estimation for binary outcomes, (2) bivariate correlation estimation for continuous outcomes, and 
    (3) estimation of component-wise means and variances under a conditional two-component Gaussian mixture model for a continuous variable stratified by a binary class label.
    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>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: stats
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-10-16 06:10:26 UTC; shanglongwen
Author: Longwen Shang [aut, cre],
  Min Tsao [aut],
  Xuekui Zhang [aut]
Maintainer: Longwen Shang <shanglongwen0918@gmail.com>
Repository: CRAN
Date/Publication: 2025-10-16 20:20:17 UTC
Built: R 4.6.0; ; 2025-11-02 02:36:48 UTC; windows
