forestBalance
Balancing Confounder Distributions with Forest Energy Balancing
Estimates average treatment effects using kernel energy balancing with random forest similarity kernels. A multivariate random forest jointly models covariates, outcome, and treatment to build a similarity kernel between observations. This kernel is then used for energy balancing to create weights that control for confounding. The method is described in De and Huling (2025) <doi:10.48550/arXiv.2512.18069>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling source/ R- | forestBalance_0.1.0.tar.gz |
318.9 KiB |
0.1.0 |
latest source/ R- | forestBalance_0.1.0.tar.gz |
318.9 KiB |
0.1.0 |
2026-04-23 source/ R- | forestBalance_0.1.0.tar.gz |
318.9 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | forestBalance_0.1.0.zip |
642.7 KiB |