covdepGE
1.0.1Covariate Dependent Graph Estimation
Overview
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.
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2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2025-11-27issues were not corrected despite reminders
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.0.12022-09-16 · diff ↗
- 1.0.02022-08-24
- RR 4.2.0 released · 2022-04-22
Package metadata
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- 2
- License
- GPL (>= 3) OSI
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