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covdepGE: Covariate Dependent Graph Estimation

A covariate-dependent approach to Gaussian graphical modeling as described in Dasgupta et al. (2022). Employs a novel weighted pseudo-likelihood approach to model the conditional dependence structure of data as a continuous function of an extraneous covariate. The main function, covdepGE::covdepGE(), estimates a graphical representation of the conditional dependence structure via a block mean-field variational approximation, while several auxiliary functions (inclusionCurve(), matViz(), and plot.covdepGE()) are included for visualizing the resulting estimates.

Version: 1.0.1
Imports: doParallel, foreach, ggplot2, glmnet, latex2exp, MASS, parallel, Rcpp, reshape2, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0), covr, vdiffr
Published: 2022-09-16
DOI: 10.32614/CRAN.package.covdepGE
Author: Jacob Helwig [cre, aut], Sutanoy Dasgupta [aut], Peng Zhao [aut], Bani Mallick [aut], Debdeep Pati [aut]
Maintainer: Jacob Helwig <jacob.a.helwig at tamu.edu>
BugReports: https://github.com/JacobHelwig/covdepGE/issues
License: GPL (≥ 3)
URL: https://github.com/JacobHelwig/covdepGE
NeedsCompilation: yes
Language: en-US
Materials: README
CRAN checks: covdepGE results

Documentation:

Reference manual: covdepGE.pdf

Downloads:

Package source: covdepGE_1.0.1.tar.gz
Windows binaries: r-devel: covdepGE_1.0.1.zip, r-release: covdepGE_1.0.1.zip, r-oldrel: covdepGE_1.0.1.zip
macOS binaries: r-release (arm64): covdepGE_1.0.1.tgz, r-oldrel (arm64): covdepGE_1.0.1.tgz, r-release (x86_64): covdepGE_1.0.1.tgz, r-oldrel (x86_64): covdepGE_1.0.1.tgz
Old sources: covdepGE archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=covdepGE to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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