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ivgls  

Network-Aware IV Regression with Graph-Fused Lasso
View on CRAN: Click here


Download and install ivgls package within the R console
Install from CRAN:
install.packages("ivgls")

Install from Github:
library("remotes")
install_github("cran/ivgls")

Install by package version:
library("remotes")
install_version("ivgls", "0.1.0")



Attach the package and use:
library("ivgls")
Maintained by
Dhrubajyoti Ghosh
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-24
Latest Update: 2026-06-24
Description:
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>.
How to cite:
Dhrubajyoti Ghosh (2026). ivgls: Network-Aware IV Regression with Graph-Fused Lasso. R package version 0.1.0, https://cran.r-project.org/web/packages/ivgls. Accessed 25 Oct. 2026.
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