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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "BayesRegDTR" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'BayesRegDTR: Bayesian Regression for Dynamic Treatment Regimes'
version: 1.1.2
doi: 10.32614/CRAN.package.BayesRegDTR
abstract: Methods to estimate optimal dynamic treatment regimes using Bayesian likelihood-based
  regression approach as described in Yu, W., & Bondell, H. D. (2023) <https://doi.org/10.1093/jrsssb/qkad016>
  Uses backward induction and dynamic programming theory for computing expected values.
  Offers options for future parallel computing.
authors:
- family-names: Lim
  given-names: Jeremy
  email: jeremylim23@gmail.com
- family-names: Yu
  given-names: Weichang
  email: weichang.yu@unimelb.edu.au
  orcid: https://orcid.org/0000-0002-0399-3779
repository: https://jlimrasc.r-universe.dev
repository-code: https://github.com/jlimrasc/BayesRegDTR
commit: 7668c9f4e735849cd61dcdab8e24ef5e25b12e33
url: https://github.com/jlimrasc/BayesRegDTR
date-released: '2025-12-01'
contact:
- family-names: Yu
  given-names: Weichang
  email: weichang.yu@unimelb.edu.au
  orcid: https://orcid.org/0000-0002-0399-3779