Package: balnet
Title: Pathwise Estimation of Covariate Balancing Propensity Scores
Version: 0.0.4
Authors@R: c(
    person("Erik", "Sverdrup", role = c("aut", "cre"), email = "erik.sverdrup@gmail.com"),
    person("Trevor", "Hastie", role = "aut"),
    person("James", "Yang", role = "ctb", comment = "Author of the bundled adelie C++ library.")
    )
Description: 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, yielding balancing weights that target
        covariate balance for the ATE and ATT. Under lasso
        penalization, lambda bounds the maximum covariate imbalance, so
        the regularization path traces a sequence of decreasing
        imbalance tolerances. For details, see Sverdrup & Hastie (2026)
        <doi:10.48550/arXiv.2602.18577>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
LinkingTo: Rcpp, RcppEigen
SystemRequirements: C++17
Imports: Rcpp, Matrix, methods
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
URL: https://github.com/erikcs/balnet
BugReports: https://github.com/erikcs/balnet/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-09-23 09:21:00 UTC; root
Author: Erik Sverdrup [aut, cre], Trevor Hastie [aut], James Yang [ctb]
        (Author of the bundled adelie C++ library.)
Maintainer: Erik Sverdrup <erik.sverdrup@gmail.com>
Repository: https://erikcs.r-universe.dev
Date/Publication: 2026-08-23 10:10:23 UTC
RemoteUrl: https://github.com/cran/balnet
RemoteRef: HEAD
RemoteSha: 5800ce783aebabb73086e5dfe8b71f399847f7ff