Package: balnet 0.0.3

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, 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>.

Authors:Erik Sverdrup [aut, cre], Trevor Hastie [aut], James Yang [ctb]