Tools for Applying Catalytic Priors in Statistical Modeling R package catalytic version 0.1.0 To improve estimation accuracy and stability in statistical modeling, catalytic prior distributions are employed, integrating observed data with synthetic data generated from a simpler model's predictive distribution. This approach enhances model robustness, stability, and flexibility in complex data scenarios. The catalytic prior distributions are introduced by 'Huang et al.' (2020, <doi:10.1073/pnas.1920913117>), Li and Huang (2023, <doi:10.48550/arXiv.2312.01411>). Software Depends: R (>= 3.5.0) Imports: coda, invgamma, rlang, rstan, stats, truncnorm, MASS, lme4, quadform, survival, methods Suggests: knitr, rmarkdown, testthat, pROC Dongming Huang <huang.dongming@nus.edu.sg> Comprehensive R Archive Network (CRAN) Yitong Wu [aut] (ORCID: <https://orcid.org/0009-0000-8683-5129>), Dongming Huang [aut, cre] (ORCID: <https://orcid.org/0000-0003-4265-7708>), Weihao Li [aut], Ministry of Education, Singapore [fnd] (The development of this package is supported by the Ministry of Education, Singapore, under the Academic Research Fund Tier 1 A-8000466-00-00 (FY2022).) MIT + file LICENSE (https://CRAN.R-project.org/package=catalytic/LICENSE) 2024-12-18 application/tgz https://CRAN.R-project.org/package=catalytic doi:10.32614/CRAN.package.catalytic