This repository contains

1. ./package The R package brar to conduct Bayesian response-adaptive randomization

2. ./paper Code and data to reproduce result from the paper: Pawel, S., Held. L. (2025). Stabilizing Thompson Sampling with Point Null Bayesian Response-Adaptive Randomization. https://doi.org/10.48550/arXiv.2510.01734

To cite our work, use the following BibTeX reference

@article{PawelHeld2025,
  year = {2025},
  author = {Samuel Pawel and Leonhard Held},
  title = {Stabilizing {Thompson} Sampling with Point Null {Bayesian} Response-Adaptive Randomization},
  url = {https://github.com/SamCH93/brar},
  doi = {10.48550/arXiv.2510.01734}
}

An interactively explorable simulation results dashboard is available at: https://samch93.github.io/brar/

Make sure to have Docker and Make installed, then run make docker-rstudio from the root directory of this git repository. This will install all necessary dependencies. RStudio Server can then be opened from a browser (http://localhost:8787), and the R scripts in /paper, for example, /paper/BFBRAR.R, which contains all code for the results from the paper), can be rerun. Make sure to change the working directory to /paper inside RStudio Server before running the R scripts. Running make docker-paper produces the paper/BFBRAR.tex file from the paper/BFBRAR.Rnw source file (dynamically inserting numbers and figures) and then compiles it to a PDF (requires a local LaTeX installation; only tested with TeX Live 2023/Debian).