diff --git a/README.Rmd b/README.Rmd index 99f7c43a..ebd12164 100644 --- a/README.Rmd +++ b/README.Rmd @@ -263,7 +263,8 @@ When using **posterior**, please cite it as follows: Working with Posterior Distributions.” R package version XXX, . -When using the MCMC convergence diagnostics `rhat`, `ess_bulk`, or `ess_tail`, +When using the MCMC convergence diagnostics `rhat`, `ess_bulk`, `ess_tail`, +`ess_median`, `ess_quantile`, `mcse_median`, or `mcse_quantile` please also cite * Vehtari A., Gelman A., Simpson D., Carpenter B., & Bürkner P. C. (2021). @@ -271,6 +272,31 @@ Rank-normalization, folding, and localization: An improved Rhat for assessing convergence of MCMC (with discussion). *Bayesian Analysis*. 16(2), 667–718. doi.org/10.1214/20-BA1221 +When using the MCMC convergence diagnostic `rhat_nested` +please also cite + +* Margossian, C. C., Hoffman, M. D., Sountsov, P., Riou-Durand, L., + Vehtari, A., and Gelman, A. (2024). + Nested $\widehat{R}$: Assessing the convergence of Markov chain + Monte Carlo when running many short chains. *Bayesian Analysis*, + doi:10.1214/24-BA1453. + +When using the MCMC convergence diagnostic `rstar` +please also cite + +* Lambert, B. and Vehtari, A. (2022). $R^*$: A robust MCMC convergence + diagnostic with uncertainty using decision tree classifiers. + *Bayesian Analysis*, 17(2):353-379. + doi:10.1214/20-BA1252 + +When using the Pareto-k diagnostics `pareto_khat`, `pareto_min_ss`, +`pareto_convergence_rate`, `khat_threshold` or `pareto_diags`, or +Pareto smoothing `pareto_smooth` please also cite + +* Vehtari, A., Simpson, D., Gelman, A., Yao, Y., and Gabry, J. (2024). +Pareto smoothed importance sampling. +*Journal of Machine Learning Research*, 25(72):1-58. + The same information can be obtained by running `citation("posterior")`. ### References @@ -279,11 +305,26 @@ Gelman A., Carlin J. B., Stern H. S., David B. Dunson D. B., Aki Vehtari A., & Rubin D. B. (2013). *Bayesian Data Analysis, Third Edition*. Chapman and Hall/CRC. +Lambert, B. and Vehtari, A. (2022). $R^*$: A robust MCMC convergence +diagnostic with uncertainty using decision tree classifiers. +*Bayesian Analysis*, 17(2):353-379. +doi:10.1214/20-BA1252 + +Margossian, C. C., Hoffman, M. D., Sountsov, P., Riou-Durand, L., +Vehtari, A., and Gelman, A. (2024). +Nested $\widehat{R}$: Assessing the convergence of Markov chain +Monte Carlo when running many short chains. *Bayesian Analysis*, +doi:10.1214/24-BA1453. + Vehtari A., Gelman A., Simpson D., Carpenter B., & Bürkner P. C. (2021). Rank-normalization, folding, and localization: An improved Rhat for assessing convergence of MCMC (with discussion). *Bayesian Analysis*. 16(2), 667–718. doi.org/10.1214/20-BA1221 +Vehtari, A., Simpson, D., Gelman, A., Yao, Y., and Gabry, J. (2024). +Pareto smoothed importance sampling. +*Journal of Machine Learning Research*, 25(72):1-58. + ### Licensing The **posterior** package is licensed under the following licenses: diff --git a/inst/CITATION b/inst/CITATION index 8f9f75dc..f92fc2ae 100644 --- a/inst/CITATION +++ b/inst/CITATION @@ -21,7 +21,64 @@ for assessing convergence of MCMC (with discussion)", person("Daniel", "Simpson"), person("Bob", "Carpenter"), person("Paul-Christian", "Bürkner")), - year = "2021", journal = "Bayesian Analysis", - header = "To cite the MCMC convergence diagnostics:" + year = "2021", + volume = "16", + number = "2", + pages = "667-718", + header = "To cite the MCMC convergence diagnostics (`rhat`, `ess_bulk`, `ess_tail`, + `ess_median`, `ess_quantile`, `mcse_median`, and `mcse_quantile`):" +) + +bibentry( + title = "Nested Rhat: Assessing the convergence of Markov chain Monte Carlo when running many short chains", + bibtype = "Article", + author = c( + person("Charles C.", "Margossian"), + person("Matthew D.", "Hoffman"), + person("Pavel", "Sountsov"), + person("Lionel", "Riou-Durand"), + person("Aki", "Vehtari"), + person("Andrew", "Gelman") + ), + journal = "Bayesian Analysis", + year = 2024, + doi = "10.1214/24-BA1453", + header = "To cite MCMC convergence diagnostic `nested_rhat`:" +) + +bibentry( + title = "Rstar: A robust MCMC convergence diagnostic with uncertainty using decision tree classifiers", + bibtype = "Article", + author = c( + person("Ben", "Lambert"), + person("Aki", "Vehtari") + ), + journal = "Bayesian Analysis", + year = 2022, + volume = 17, + number = 2, + pages = "353-379", + doi = "10.1214/20-BA1252", + header = "To cite MCMC convergence diagnostic `rstar`:" +) + +bibentry( + title = "Pareto smoothed importance sampling", + bibtype = "Article", + author = c( + person("Aki", "Vehtari"), + person("Daniel", "Simpson"), + person("Andrew", "Gelman"), + person("Yuling", "Yao"), + person("Jonah", "Gabry") + ), + journal = "Journal of Machine Learning Research", + year = 2024, + volume = 25, + number = 72, + pages = "1-58", + header = "To cite Pareto-k diagnostics and Pareto smoothing (`pareto_khat`, `pareto_min_ss`, +`pareto_convergence_rate`, `khat_threshold`, `pareto_diags`, and +`pareto_smooth`):" )