balnet: Pathwise Estimation of Covariate Balancing Propensity Scores

Provides pathwise estimation of regularized logistic propensity score models using covariate balancing loss functions rather than maximum likelihood. Regularization paths are fit via the 'adelie' elastic-net solver with a 'glmnet'-like interface and objectives that directly target covariate balance for the ATE and ATT. For details, see Sverdrup & Hastie (2026) <doi:10.48550/arXiv.2602.18577>.

Version: 0.0.1
Imports: Rcpp, Matrix, methods
LinkingTo: Rcpp, RcppEigen
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2026-04-03
DOI: 10.32614/CRAN.package.balnet (may not be active yet)
Author: Erik Sverdrup [aut, cre], Trevor Hastie [aut], James Yang [ctb] (adelie core author)
Maintainer: Erik Sverdrup <erik.sverdrup at monash.edu>
BugReports: https://github.com/erikcs/balnet/issues
License: MIT + file LICENSE
URL: https://github.com/erikcs/balnet
NeedsCompilation: yes
SystemRequirements: C++17
CRAN checks: balnet results

Documentation:

Reference manual: balnet.html , balnet.pdf
Vignettes: An introduction to balnet (source, R code)

Downloads:

Package source: balnet_0.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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