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:

References in zbMATH (referenced in 345 articles )

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  1. Golightly, Andrew; Sherlock, Chris: Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes (2022)
  2. Gonçalves, Kelly C. M.; Ghosh, Malay: Unit level model for small area estimation with count data under square root transformation (2022)
  3. Irena B Chen, Qiyuan Shi, Scott L Zeger, Zhenke Wu: baker: An R package for Nested Partially-Latent Class Models (2022) arXiv
  4. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2022)
  5. Zhou, Haiming; Huang, Xianzheng: Bayesian beta regression for bounded responses with unknown supports (2022)
  6. Alberto Caimo, Lampros Bouranis, Robert Krause, Nial Friel: Statistical Network Analysis with Bergm (2021) arXiv
  7. Bartlett, Thomas E.; Kosmidis, Ioannis; Silva, Ricardo: Two-way sparsity for time-varying networks with applications in genomics (2021)
  8. Bhattarai, Saroj; Chatterjee, Arpita; Park, Woong Yong: Effects of US quantitative easing on emerging market economies (2021)
  9. 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
  10. Capdeville, Vitor; Gonçalves, Kelly C. M.; Pereira, João B. M.: Bayesian factor models for multivariate categorical data obtained from questionnaires (2021)
  11. 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)
  12. Corradin, R., Canale, A.,Nipoti, B: BNPmix: An R Package for Bayesian Nonparametric Modeling via Pitman-Yor Mixtures (2021) not zbMATH
  13. Elshahhat, Ahmed; Nassar, Mazen: Bayesian survival analysis for adaptive type-II progressive hybrid censored hjorth data (2021)
  14. Erler, N. S., Rizopoulos, D., Lesaffre, E. M. E. H.: JointAI: Joint Analysis and Imputation of Incomplete Data in R (2021) not zbMATH
  15. Ferreira, Marco A. R.; Porter, Erica M.; Franck, Christopher T.: Fast and scalable computations for Gaussian hierarchical models with intrinsic conditional autoregressive spatial random effects (2021)
  16. Francesco Denti: intRinsic: an R package for model-based estimation of the intrinsic dimension of a dataset (2021) arXiv
  17. Gregor Zens, Sylvia Frühwirth-Schnatter, Helga Wagner: Efficient Bayesian Modeling of Binary and Categorical Data in R: The UPG Package (2021) arXiv
  18. Holbrook, Andrew J.; Loeffler, Charles E.; Flaxman, Seth R.; Suchard, Marc A.: Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data (2021)
  19. Hosszejni, D.; Kastner, G: Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol (2021) not zbMATH
  20. Jean-Paul Fox, Konrad Klotzke, Rinke Klein Entink: LNIRT: An R Package for Joint Modeling of Response Accuracy and Times (2021) arXiv

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