rjags

R package rjags: Bayesian graphical models using MCMC. Interface to the JAGS MCMC library. The rjags package provides an interface from R to the JAGS library for Bayesian data analysis. JAGS uses Markov Chain Monte Carlo (MCMC) to generate a sequence of dependent samples from the posterior distribution of the parameters.


References in zbMATH (referenced in 64 articles )

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  1. Manderson, Andrew A.; Goudie, Robert J. B.: A numerically stable algorithm for integrating Bayesian models using Markov melding (2022)
  2. Nathan Green, Anna Heath, Gianluca Baio: BCEA: An R Package for Cost-Effectiveness Analysis (2022) arXiv
  3. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2022)
  4. Bonner, S., Kim, H.-N., Westneat, D., Mutzel, A., Wright, J., Schofield, M.: dalmatian: A Package for Fitting Double Hierarchical Linear Models in R via JAGS and nimble (2021) not zbMATH
  5. Brandon P.M. Edwards, Adam C. Smith: bbsBayes: An R Package for Hierarchical Bayesian Analysis of North American Breeding Bird Survey Data (2021) not zbMATH
  6. Chao, Fengqing; Gerland, Patrick; Cook, Alex R.; Alkema, Leontine: Global estimation and scenario-based projections of sex ratio at birth and missing female births using a Bayesian hierarchical time series mixture model (2021)
  7. Eggleston, B. S., Ibrahim, J. G., McNeil, B., Catellier, D: BayesCTDesign: An R Package for Bayesian Trial Design Using Historical Control Data (2021) not zbMATH
  8. Erler, N. S., Rizopoulos, D., Lesaffre, E. M. E. H.: JointAI: Joint Analysis and Imputation of Incomplete Data in R (2021) not zbMATH
  9. Nieto-Barajas, Luis E.; Targino, Rodrigo S.: A gamma moving average process for modelling dependence across development years in run-off triangles (2021)
  10. Perry de Valpine, Sally Paganin, Daniel Turek: compareMCMCs: An R package for studying MCMC efficiency (2021) not zbMATH
  11. Suchit Mehrotra, Arnab Maity: Variational Inference for Shrinkage Priors: The R package vir (2021) arXiv
  12. Umlauf, N., Klein, N., Simon, T., Zeileis, A: bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond) (2021) not zbMATH
  13. Anne Philippe, Marie-Anne Vibet: Analysis of Archaeological Phases Using the R Package ArchaeoPhases (2020) not zbMATH
  14. David, Olivier; van Frank, Gaëlle; Goldringer, Isabelle; Rivière, Pierre; Turbet Delof, Michel: Bayesian inference of natural selection from spatiotemporal phenotypic data (2020)
  15. Hashimoto, E. M.; Ortega, E. M. M.; Cordeiro, G. M.; Suzuki, A. K.; Kattan, M. W.: The multinomial logistic regression model for predicting the discharge status after liver transplantation: estimation and diagnostics analysis (2020)
  16. Oravecz, Zita; Vandekerckhove, Joachim: A joint process model of consensus and longitudinal dynamics (2020)
  17. Osthus, Dave; Hyman, Jeffrey D.; Karra, Satish; Panda, Nishant; Srinivasan, Gowri: A probabilistic clustering approach for identifying primary subnetworks of discrete fracture networks with quantified uncertainty (2020)
  18. Amoros, Ruben; King, Ruth; Toyoda, Hidenori; Kumada, Takashi; Johnson, Philip J.; Bird, Thomas G.: A continuous-time hidden Markov model for cancer surveillance using serum biomarkers with application to hepatocellular carcinoma (2019)
  19. Arellano-Valle, Reinaldo B.; Contreras-Reyes, Javier E.; Quintero, Freddy O. López; Valdebenito, Abel: A skew-normal dynamic linear model and Bayesian forecasting (2019)
  20. Gilles Kratzer, Fraser Iain Lewis, Arianna Comin, Marta Pittavino, Reinhard Furrer: Additive Bayesian Network Modelling with the R Package abn (2019) arXiv

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