Mcmcpack

MCMCpack: Markov chain Monte Carlo (MCMC) Package. This package contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return coda mcmc objects that can then be summarized using the coda package. MCMCpack also contains some useful utility functions, including some additional density functions and pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization.


References in zbMATH (referenced in 37 articles )

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  1. Bouranis, Lampros; Friel, Nial; Maire, Florian: Model comparison for Gibbs random fields using noisy reversible jump Markov chain Monte Carlo (2018)
  2. Edgar Merkle; Yves Rosseel: blavaan: Bayesian Structural Equation Models via Parameter Expansion (2018) not zbMATH
  3. Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W.; Minin, Vladimir N.; Suchard, Marc A.: Birth/birth-death processes and their computable transition probabilities with biological applications (2018)
  4. Mair, Patrick: Modern psychometrics with R (2018)
  5. Okada, Kensuke; Mayekawa, Shin-ichi: Post-processing of Markov chain Monte Carlo output in Bayesian latent variable models with application to multidimensional scaling (2018)
  6. Parisi, Antonio; Liseo, B.: Objective Bayesian analysis for the multivariate skew-(t) model (2018)
  7. Wagner Bonat: Multiple Response Variables Regression Models in R: The mcglm Package (2018) not zbMATH
  8. Brunero Liseo, Antonio Parisi: Objective Bayesian analysis for the multivariate skew-t model (2017) arXiv
  9. Chen Dong; Michel Wedel: BANOVA: An R Package for Hierarchical Bayesian ANOVA (2017) not zbMATH
  10. Dries Benoit and Dirk Van den Poel: bayesQR: A Bayesian Approach to Quantile Regression (2017) not zbMATH
  11. Härdle, Karl Wolfgang; Okhrin, Ostap; Okhrin, Yarema: Basic elements of computational statistics (2017)
  12. Mauricio Sarrias and Ricardo Daziano: Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package (2017) not zbMATH
  13. Nalan Baştürk and Stefano Grassi and Lennart Hoogerheide and Anne Opschoor and Herman van Dijk: The R Package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference (2017) not zbMATH
  14. Schaarschmidt, Frank; Gerhard, Daniel; Vogel, Charlotte: Simultaneous confidence intervals for comparisons of several multinomial samples (2017)
  15. Bayerstadler, Andreas; van Dijk, Linda; Winter, Fabian: Bayesian multinomial latent variable modeling for fraud and abuse detection in health insurance (2016)
  16. Leung, Dennis; Drton, Mathias: Order-invariant prior specification in Bayesian factor analysis (2016)
  17. Xavier Fernández-i-Marín: ggmcmc: Analysis of MCMC Samples and Bayesian Inference (2016) not zbMATH
  18. Bernhardt, Paul W.; Zhang, Daowen; Wang, Huixia Judy: A fast EM algorithm for Fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits (2015)
  19. Khandoker Bakar; Sujit Sahu: spTimer: Spatio-Temporal Bayesian Modeling Using R (2015) not zbMATH
  20. Bernhardt, Paul W.; Wang, Huixia Judy; Zhang, Daowen: Flexible modeling of survival data with covariates subject to detection limits via multiple imputation (2014)

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