One-dimensional examples | Location shift | Scale difference | Fit the models | Inspect fitted objects | Convergence | Estimated density ratios | Two-dimensional examples | Global shift | Local shift | Practical notes | References
Package: BATTS 0.4.0
Naoki Awaya
BATTS: Boosting and Bayesian Additive Trees for Two-Sample Comparison
Implements boosting and Bayesian additive tree methods for two-sample comparison through density ratio estimation, following Awaya, Xu, and Ma (2025) <doi:10.48550/arXiv.2508.03059>. The package supports both point estimation and uncertainty quantification via Bayesian additive tree ensembles.
Authors:
BATTS_0.4.0.tar.gz
BATTS_0.4.0.zip(r-4.7-x86_64)BATTS_0.4.0.zip(r-4.7-arm64)BATTS_0.4.0.zip(r-4.6-x86_64)BATTS_0.4.0.zip(r-4.6-arm64)
BATTS_0.4.0.tar.gz(r-4.7-arm64)BATTS_0.4.0.tar.gz(r-4.7-x86_64)BATTS_0.4.0.tar.gz(r-4.6-arm64)BATTS_0.4.0.tar.gz(r-4.6-x86_64)
BATTS_0.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
BATTS/json (API)
| # Install 'BATTS' in R: |
| install.packages('BATTS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/nawaya040/batts/issues
Last updated from:d2c58a1f7e. Checks:10 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 144 | ||
| linux-devel-x86_64 | OK | 124 | ||
| source / vignettes | OK | 241 | ||
| linux-release-arm64 | OK | 105 | ||
| linux-release-x86_64 | OK | 134 | ||
| windows-devel-arm64 | OK | 235 | ||
| windows-devel-x86_64 | OK | 260 | ||
| windows-release-arm64 | OK | 226 | ||
| windows-release-x86_64 | OK | 208 | ||
| wasm-release | OK | 100 |
Exports:bart_controlbattsbatts_bartbatts_boostboost_controlbootsdensity_ratioeval_balance_weight
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Boosting and Bayesian Additive Trees for Two-Sample Comparison | BATTS-package BATTS |
| Settings for Bayesian additive tree fits | bart_control |
| Fit a two-sample density ratio by Bayesian additive trees | batts_bart |
| Fit a two-sample density ratio by boosting | batts_boost |
| Methods for BATTS fits | batts-methods nobs.batts_fit print.batts_bart print.batts_boost print.summary.batts_fit summary.batts_fit |
| Plot a BATTS fit | batts-plot plot.batts_bart plot.batts_boost |
| Predict balancing weights and density ratios | batts-predict fitted.batts_bart fitted.batts_boost predict.batts_bart predict.batts_boost |
| Settings for boosting fits | boost_control |
| Density ratio of a fitted BATTS model | density_ratio density_ratio.batts_fit |