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 359 articles )

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  1. Canale, Antonio; Corradin, Riccardo; Nipoti, Bernardo: Importance conditional sampling for Pitman-Yor mixtures (2022)
  2. Dongyoung Go, Jina Park, Ickhoon Jin, Minjeong Jeon: lsirm12pl: An R package for latent space item response modeling (2022) arXiv
  3. dos Santos Junior, Paulo Cerqueira; Schneider, Silvana: Power piecewise exponential model for interval-censored data (2022)
  4. Golightly, Andrew; Sherlock, Chris: Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes (2022)
  5. Gonçalves, Kelly C. M.; Ghosh, Malay: Unit level model for small area estimation with count data under square root transformation (2022)
  6. Heiner, Matthew; Kottas, Athanasios: Estimation and selection for high-order Markov chains with Bayesian mixture transition distribution models (2022)
  7. Holbrook, Andrew J.; Ji, Xiang; Suchard, Marc A.: Bayesian mitigation of spatial coarsening for a Hawkes model applied to gunfire, wildfire and viral contagion (2022)
  8. Irena B Chen, Qiyuan Shi, Scott L Zeger, Zhenke Wu: baker: An R package for Nested Partially-Latent Class Models (2022) arXiv
  9. Liu, Ying; Vats, Dootika; Flegal, James M.: Batch size selection for variance estimators in MCMC (2022)
  10. Li, Yuliang; Ni, Yang; Rubin, Leah H.; Spence, Amanda B.; Xu, Yanxun: Bagel: a Bayesian graphical model for inferring drug effect longitudinally on depression in people with HIV (2022)
  11. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2022)
  12. Wehrhahn, Claudia; Barrientos, Andrés F.; Jara, Alejandro: Dependent Bayesian nonparametric modeling of compositional data using random Bernstein polynomials (2022)
  13. Yamaguchi, Kazuhiro; Templin, Jonathan: A Gibbs sampling algorithm with monotonicity constraints for diagnostic classification models (2022)
  14. Zhou, Haiming; Huang, Xianzheng: Bayesian beta regression for bounded responses with unknown supports (2022)
  15. Alberto Caimo, Lampros Bouranis, Robert Krause, Nial Friel: Statistical Network Analysis with Bergm (2021) arXiv
  16. Bartlett, Thomas E.; Kosmidis, Ioannis; Silva, Ricardo: Two-way sparsity for time-varying networks with applications in genomics (2021)
  17. Bhattarai, Saroj; Chatterjee, Arpita; Park, Woong Yong: Effects of US quantitative easing on emerging market economies (2021)
  18. 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
  19. Capdeville, Vitor; Gonçalves, Kelly C. M.; Pereira, João B. M.: Bayesian factor models for multivariate categorical data obtained from questionnaires (2021)
  20. Çetinkaya, Çağatay; Genc, Ali: On the reliability characteristics of the standard two-sided power distribution (2021)

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