ivgls: Network-Aware IV Regression with Graph-Fused Lasso
Implements network-aware instrumental variable regression for causal node discovery in high-dimensional settings with graph-structured exposures. Provides IVGL and IVGL-S estimators combining graph-Laplacian penalization with IV-based identification, including correction for invalid instruments via a sisVIVE-style update. Methods are described in Pal and Ghosh (2026) <doi:10.48550/arXiv.2604.24969>. The 'glmgraph' package, required for the main estimators, is available at the additional repository <https://djghosh1123.r-universe.dev>.
| Version: | 0.1.0 |
| Imports: | glmnet, MASS, igraph |
| Suggests: | knitr, glmgraph, rmarkdown, testthat (≥ 3.0.0), ggplot2, spelling |
| Published: | 2026-06-24 |
| DOI: | 10.32614/CRAN.package.ivgls (may not be active yet) |
| Author: | Dhrubajyoti Ghosh 
[aut, cre],
Samhita Pal [aut] |
| Maintainer: | Dhrubajyoti Ghosh <dghosh3 at kennesaw.edu> |
| BugReports: | https://github.com/djghosh1123/ivgls/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/djghosh1123/ivgls |
| NeedsCompilation: | no |
| Additional_repositories: | https://djghosh1123.r-universe.dev |
| Language: | en-US |
| Materials: | README |
| CRAN checks: | ivgls results |
Documentation:
| Reference manual: | ivgls.html , ivgls.pdf |
| Vignettes: |
Getting Started with ivgls (source, R code) |
Downloads:
| Package source: | ivgls_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: ivgls_0.1.0.zip, r-oldrel: not available |
| macOS binaries: | r-release (arm64): ivgls_0.1.0.tgz, r-oldrel (arm64): ivgls_0.1.0.tgz, r-release (x86_64): ivgls_0.1.0.tgz, r-oldrel (x86_64): ivgls_0.1.0.tgz |
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