balnet
0.0.3Pathwise Estimation of Covariate Balancing Propensity Scores
Overview
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.
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- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-04-2212 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1811 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-04-089 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-04-044 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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Checks run against github.com/erikcs/balnet on 2026-07-19.
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3 releases. R releases are shown for context.
- 0.0.3Latest
- 0.0.22026-05-05 · diff ↗
- RR 4.6.0 released · 2026-04-24
- 0.0.12026-04-03
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-04-03
- Total releases
- 3 / 1 yrs
- License
- MIT + file LICENSE OSI
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- not tracked yet
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- not tracked yet