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cff-version: 1.2.0
message: 'To cite package "covdepGE" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'covdepGE: Covariate Dependent Graph Estimation'
version: 1.0.1
doi: 10.32614/CRAN.package.covdepGE
abstract: 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.
authors:
- family-names: Helwig
  given-names: Jacob
  email: jacob.a.helwig@tamu.edu
- family-names: Dasgupta
  given-names: Sutanoy
  email: sutanoy@stat.tamu.edu
- family-names: Zhao
  given-names: Peng
  email: pzhao@stat.tamu.edu
- family-names: Mallick
  given-names: Bani
  email: bmallick@stat.tamu.edu
- family-names: Pati
  given-names: Debdeep
  email: debdeep@stat.tamu.edu
repository: https://CRAN.R-project.org/package=covdepGE
repository-code: https://github.com/JacobHelwig/covdepGE
url: https://github.com/JacobHelwig/covdepGE
date-released: '2022-09-16'
contact:
- family-names: Helwig
  given-names: Jacob
  email: jacob.a.helwig@tamu.edu