Balancing Confounder Distributions with Forest Energy Balancing
Overview
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.
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Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-04-22
- ERROR12 OK, 1 ERROR2026-04-18
- OK6 OK2026-04-08
Documentation
- Help pages
- 11includes a package overview page
- Examples that run
- 11%1 run in a plain check · 8 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 27%
Downloads
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Dependencies
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- 0.1.0Latest2026-04-07 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-04-07
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Download size
- 320 KB
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