To cite the posterior R package:
Bürkner P, Gabry J, Kay M, Vehtari A (2025). “posterior: Tools for Working with Posterior Distributions.” R package version 1.6.1, https://mc-stan.org/posterior/.
To cite the MCMC convergence diagnostics (`rhat`, `ess_bulk`, `ess_tail`, `ess_median`, `ess_quantile`, `mcse_median`, and `mcse_quantile`):
Vehtari A, Gelman A, Simpson D, Carpenter B, Bürkner P (2021). “Rank-normalization, folding, and localization: An improved Rhat for assessing convergence of MCMC (with discussion).” Bayesian Analysis, 16(2), 667-718.
To cite MCMC convergence diagnostic `nested_rhat`:
Margossian C, Hoffman M, Sountsov P, Riou-Durand L, Vehtari A, Gelman A (2024). “Nested Rhat: Assessing the convergence of Markov chain Monte Carlo when running many short chains.” Bayesian Analysis. doi:10.1214/24-BA1453.
To cite MCMC convergence diagnostic `rstar`:
Lambert B, Vehtari A (2022). “Rstar: A robust MCMC convergence diagnostic with uncertainty using decision tree classifiers.” Bayesian Analysis, 17(2), 353-379. doi:10.1214/20-BA1252.
To cite Pareto-k diagnostics and Pareto smoothing (`pareto_khat`, `pareto_min_ss`, `pareto_convergence_rate`, `khat_threshold`, `pareto_diags`, and `pareto_smooth`):
Vehtari A, Simpson D, Gelman A, Yao Y, Gabry J (2024). “Pareto smoothed importance sampling.” Journal of Machine Learning Research, 25(72), 1-58.
Corresponding BibTeX entries:
@Misc{, title = {posterior: Tools for Working with Posterior Distributions}, author = {Paul-Christian Bürkner and Jonah Gabry and Matthew Kay and Aki Vehtari}, year = {2025}, note = {R package version 1.6.1}, url = {https://mc-stan.org/posterior/}, }
@Article{, title = {Rank-normalization, folding, and localization: An improved Rhat for assessing convergence of MCMC (with discussion)}, author = {Aki Vehtari and Andrew Gelman and Daniel Simpson and Bob Carpenter and Paul-Christian Bürkner}, journal = {Bayesian Analysis}, year = {2021}, volume = {16}, number = {2}, pages = {667-718}, }
@Article{, title = {Nested Rhat: Assessing the convergence of Markov chain Monte Carlo when running many short chains}, author = {Charles C. Margossian and Matthew D. Hoffman and Pavel Sountsov and Lionel Riou-Durand and Aki Vehtari and Andrew Gelman}, journal = {Bayesian Analysis}, year = {2024}, doi = {10.1214/24-BA1453}, }
@Article{, title = {Rstar: A robust MCMC convergence diagnostic with uncertainty using decision tree classifiers}, author = {Ben Lambert and Aki Vehtari}, journal = {Bayesian Analysis}, year = {2022}, volume = {17}, number = {2}, pages = {353-379}, doi = {10.1214/20-BA1252}, }
@Article{, title = {Pareto smoothed importance sampling}, author = {Aki Vehtari and Daniel Simpson and Andrew Gelman and Yuling Yao and Jonah Gabry}, journal = {Journal of Machine Learning Research}, year = {2024}, volume = {25}, number = {72}, pages = {1-58}, }