Network-Aware IV Regression with Graph-Fused Lasso R package ivgls version 0.1.0 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>. Software Imports: glmnet, MASS, igraph Suggests: knitr, glmgraph, rmarkdown, testthat (>= 3.0.0), ggplot2, spelling Dhrubajyoti Ghosh <dghosh3@kennesaw.edu> Comprehensive R Archive Network (CRAN) Dhrubajyoti Ghosh [aut, cre] (ORCID: <https://orcid.org/0000-0002-3360-3786>), Samhita Pal [aut] (ORCID: <https://orcid.org/0009-0001-4930-916X>) MIT + file LICENSE (https://CRAN.R-project.org/package=ivgls/LICENSE) 2026-06-24 application/tgz https://CRAN.R-project.org/package=ivgls doi:10.32614/CRAN.package.ivgls en-US