README.bib

@article{
 cook2006,
 ISSN = {10618600},
 URL = {http://www.jstor.org/stable/27594203},
 abstract = {This article presents a simulation-based method designed to establish the computational correctness of software developed to fit a specific Bayesian model, capitalizing on properties of Bayesian posterior distributions. We illustrate the validation technique with two examples. The validation method is shown to find errors in software when they exist and, moreover, the validation output can be informative about the nature and location of such errors. We also compare our method with that of an earlier approach.},
 author = {Samantha R. Cook and Andrew Gelman and Donald B. Rubin},
 journal = {Journal of Computational and Graphical Statistics},
 number = {3},
 pages = {675--692},
 publisher = {[American Statistical Association, Taylor & Francis, Ltd., Institute of Mathematical Statistics, Interface Foundation of America]},
 title = {Validation of Software for Bayesian Models Using Posterior Quantiles},
 volume = {15},
 year = {2006}
}

@article{talts2020,
      title={Validating Bayesian Inference Algorithms with Simulation-Based Calibration}, 
      author={Sean Talts and Michael Betancourt and Daniel Simpson and Aki Vehtari and Andrew Gelman},
      year={2020},
      eprint={1804.06788},
      archivePrefix={arXiv},
      primaryClass={stat.ME}
}