R package bayesplot. Plotting for Bayesian Models. Plotting functions for posterior analysis, model checking, and MCMC diagnostics. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with Stan.

References in zbMATH (referenced in 9 articles )

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  1. Edgar Santos-Fernandez, Jay M. Ver Hoef, James M. McGree, Daniel J. Isaak, Kerrie Mengersen, Erin E. Peterson: SSNbayes: An R package for Bayesian spatio-temporal modelling on stream networks (2022) arXiv
  2. Merkle, E. C., Fitzsimmons, E., Uanhoro, J., Goodrich, B. : Efficient Bayesian Structural Equation Modeling in Stan (2021) not zbMATH
  3. Sergio Venturini, Raffaella Piccarreta : A Bayesian Approach for Model-Based Clustering of Several Binary Dissimilarity Matrices: The dmbc Package in R (2021) not zbMATH
  4. Weber, S., Li, Y., Seaman III, J. W., Kakizume, T., Schmidli, H.: Applying Meta-Analytic-Predictive Priors with the R Bayesian Evidence Synthesis Tools (2021) not zbMATH
  5. Izhar Asael Alonzo Matamoros, Cristian Andres Cruz Torres: varstan: An R package for Bayesian analysis of structured time series models with Stan (2020) arXiv
  6. Antonio Calcagnì, Massimiliano Pastore, Gianmarco Altoè: ssMousetrack: Analysing computerized tracking data via Bayesian state-space models in R (2019) arXiv
  7. Shana Scogin; Johannes Karreth; Andreas Beger; Rob Williams: BayesPostEst: An R Package to Generate Postestimation Quantities for Bayesian MCMC Estimation (2019) not zbMATH
  8. Adam Peterson, Brisa Sanchez: rstap: An R Package for Spatial Temporal Aggregated Predictor Models (2018) arXiv
  9. Paul-Christian Buerkner: Bayesian Distributional Non-Linear Multilevel Modeling with the R Package brms (2017) arXiv