CODA

R package coda: Output analysis and diagnostics for MCMC , Output analysis and diagnostics for Markov Chain Monte Carlo simulations. Provides functions for summarizing and plotting the output from Markov Chain Monte Carlo (MCMC) simulations, as well as diagnostic tests of convergence to the equilibrium distribution of the Markov chain. (Source: http://cran.r-project.org/web/packages)


References in zbMATH (referenced in 180 articles )

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  1. Chanialidis, Charalampos; Evers, Ludger; Neocleous, Tereza; Nobile, Agostino: Efficient Bayesian inference for COM-Poisson regression models (2018)
  2. Chitakasempornkul, Kessinee; Sanderson, Michael W.; Cha, Elva; Renter, David G.; Jager, Abigail; Bello, Nora M.: Accounting for data architecture on structural equation modeling of feedlot cattle performance (2018)
  3. Chris Groendyke; David Welch: epinet: An R Package to Analyze Epidemics Spread across Contact Networks (2018) not zbMATH
  4. Cowles, Mary Kathryn; Bonett, Stephen; Seedorff, Michael: Independent sampling for Bayesian normal conditional autoregressive models with OpenCL acceleration (2018)
  5. Depaoli, Sarah; Liu, Yang: Book review of: R. Levy and R. J. Mislevy, Bayesian psychometric modeling (2018)
  6. Drovandi, Christopher C.; Moores, Matthew T.; Boys, Richard J.: Accelerating pseudo-marginal MCMC using Gaussian processes (2018)
  7. Duncan Lee; Alastair Rushworth; Gary Napier: Spatio-Temporal Areal Unit Modeling in R with Conditional Autoregressive Priors Using the CARBayesST Package (2018) not zbMATH
  8. Erbisti, Rafael S.; Fonseca, Thais C. O.; Alves, Mariane B.: Covariance modeling for multivariate spatial processes based on separable approximations (2018)
  9. Georgios Papageorgiou: BNSP: an R Package for Fitting Bayesian Regression Models With Semiparametric Mean and Variance Functions (2018) arXiv
  10. Gómez-Rubio, Virgilio; Rue, Håvard: Markov chain Monte Carlo with the integrated nested Laplace approximation (2018)
  11. Kamatani, Kengo: Efficient strategy for the Markov chain Monte Carlo in high-dimension with heavy-tailed target probability distribution (2018)
  12. Leisen, Fabrizio; Rossini, Luca; Villa, Cristiano: Objective Bayesian analysis of the Yule-Simon distribution with applications (2018)
  13. Link, William A.; Converse, Sarah J.; Yackel Adams, Amy A.; Hostetter, Nathan J.: Analysis of population change and movement using robust design removal data (2018)
  14. Mastrantonio, Gianluca: The joint projected normal and skew-normal: a distribution for poly-cylindrical data (2018)
  15. Mathieu Carmassi; Pierre Barbillon; Matthieu Chiodetti; Merlin Keller; Eric Parent: CaliCo: a R package for Bayesian calibration (2018) arXiv
  16. Sadinle, Mauricio: Bayesian propagation of record linkage uncertainty into population size estimation of human rights violations (2018)
  17. Zhou, Haiming; Hanson, Timothy: A unified framework for Fitting Bayesian semiparametric models to arbitrarily censored survival data, including spatially referenced data (2018)
  18. Andrianakis, Ioannis; McCreesh, Nicky; Vernon, Ian; McKinley, Trevelyan J.; Oakley, Jeremy E.; Nsubuga, Rebecca N.; Goldstein, Michael; White, Richard G.: Efficient history matching of a high dimensional individual-based HIV transmission model (2017)
  19. Antonio Canale: msBP: An R Package to Perform Bayesian Nonparametric Inference Using Multiscale Bernstein Polynomials Mixtures (2017) not zbMATH
  20. Bob Carpenter and Andrew Gelman and Matthew Hoffman and Daniel Lee and Ben Goodrich and Michael Betancourt and Marcus Brubaker and Jiqiang Guo and Peter Li and Allen Riddell: Stan: A Probabilistic Programming Language (2017) not zbMATH

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