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 62 articles )

Showing results 41 to 60 of 62.
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  1. Alhamzawi, Rahim: Model selection in quantile regression models (2015)
  2. Alhamzawi, Rahim; Yu, Keming: Bayesian Tobit quantile regression using (g)-prior distribution with ridge parameter (2015)
  3. 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)
  4. Khandoker Bakar; Sujit Sahu: spTimer: Spatio-Temporal Bayesian Modeling Using R (2015) not zbMATH
  5. Bernhardt, Paul W.; Wang, Huixia Judy; Zhang, Daowen: Flexible modeling of survival data with covariates subject to detection limits via multiple imputation (2014)
  6. Macaro, Christian; Prado, Raquel: Spectral decompositions of multiple time series: a Bayesian non-parametric approach (2014)
  7. Scherer, Ralph; Schaarschmidt, Frank; Prescher, Sabine; Priesnitz, Kai U.: Simultaneous confidence intervals for comparing biodiversity indices estimated from overdispersed count data (2013)
  8. Aston, John A. D.; Peng, J. Y.; Martin, Donald E. K.: Implied distributions in multiple change point problems (2012)
  9. Ji, Yonggang; Lin, Nan; Zhang, Baoxue: Model selection in binary and Tobit quantile regression using the Gibbs sampler (2012)
  10. Kaplan, David; Chen, Jianshen: A two-step Bayesian approach for propensity score analysis: simulations and case study (2012)
  11. Klein, Martin; Neerchal, Nagaraj; Sinha, Bimal; Chiu, Weihsueh; White, Paul: Statistical inferences from serially correlated methylene chloride data (2012)
  12. R. Chalmers: mirt: A Multidimensional Item Response Theory Package for the R Environment (2012) not zbMATH
  13. Paul De Boeck; Marjan Bakker; Robert Zwitser; Michel Nivard; Abe Hofman; Francis Tuerlinckx; Ivailo Partchev: The Estimation of Item Response Models with the lmer Function from the lme4 Package in R (2011) not zbMATH
  14. Anand Patil; David Huard; Christopher Fonnesbeck: PyMC: Bayesian Stochastic Modelling in Python (2010) not zbMATH
  15. Macaro, Christian: Bayesian non-parametric signal extraction for Gaussian time series (2010)
  16. Nott, David J.; Leng, Chenlei: Bayesian projection approaches to variable selection in generalized linear models (2010)
  17. Raftery, Adrian E.; Bao, Le: Estimating and projecting trends in HIV/AIDS generalized epidemics using incremental mixture importance sampling (2010)
  18. Gelman, Andrew; Jakulin, Aleks; Pittau, Maria Grazia; Su, Yu-Sung: A weakly informative default prior distribution for logistic and other regression models (2008)
  19. Fahrmeir, Ludwig; Raach, Alexander: A Bayesian semiparametric latent variable model for mixed responses (2007)
  20. Rosenthal, Jeffrey S.: AMCMC: an R interface for adaptive MCMC (2007)