R2WinBUGS

R2WinBUGS: Running WinBUGS and OpenBUGS from R / S-PLUS , Using this package, it is possible to call a BUGS model, summarize inferences and convergence in a table and graph, and save the simulations in arrays for easy access in R / S-PLUS. In S-PLUS, the openbugs functionality and the windows emulation functionality is not yet available. (Source: http://cran.r-project.org/web/packages)


References in zbMATH (referenced in 70 articles , 1 standard article )

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  1. Oǧuz-Alper, Melike; Berger, Yves G.: Modelling multilevel data under complex sampling designs: an empirical likelihood approach (2020)
  2. Amaral Turkman, Maria Antónia; Paulino, Carlos Daniel; Müller, Peter: Computational Bayesian statistics. An introduction (2019)
  3. Conversano, Claudio; Cannas, Massimo; Mola, Francesco; Sironi, Emiliano: Random effects clustering in multilevel modeling: choosing a proper partition (2019)
  4. George G Vega Yon; Paul Marjoram: fmcmc: A friendly MCMC framework (2019) not zbMATH
  5. Haziq Jamil, Wicher Bergsma: iprior: An R Package for Regression Modelling using I-priors (2019) arXiv
  6. Li, Yong; Yu, Jun; Zeng, Tao: Hypothesis testing, specification testing, and model selection based on the MCMC output using R (2019)
  7. Cowles, Mary Kathryn; Bonett, Stephen; Seedorff, Michael: Independent sampling for Bayesian normal conditional autoregressive models with OpenCL acceleration (2018)
  8. Jing Zhao; Jian’an Luan; Peter Congdon: Bayesian Linear Mixed Models with Polygenic Effects (2018) not zbMATH
  9. Ariza-Hernandez, Francisco J.; Sanchez-Ortiz, Jorge; Arciga-Alejandre, Martin P.; Vivas-Cruz, Luis X.: Bayesian analysis for a fractional population growth model (2017)
  10. Barrado, Leandro García; Coart, Els; Burzykowski, Tomasz: Estimation of diagnostic accuracy of a combination of continuous biomarkers allowing for conditional dependence between the biomarkers and the imperfect reference-test (2017)
  11. Ganjali, M.; Moradzadeh, N.; Baghfalaki, T.: Bayesian testing of agreement criteria under order constraints (2017)
  12. Janani, Leila; Mansournia, Mohammad Ali; Mohammad, Kazem; Mahmoodi, Mahmood; Mehrabani, Kamran; Nourijelyani, Keramat: Comparison between Bayesian approach and frequentist methods for estimating relative risk in randomized controlled trials: a simulation study (2017)
  13. Mohsenkhani, Zohreh Fallah; Mohammadzadeh, Mohsen: Augmented mixed beta regression and modeling of employed proportions in households (2017)
  14. Thanoon, Thanoon Y.; Adnan, Robiah: Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data (2017)
  15. Elghafghuf, Adel; Stryhn, Henrik: Correlated versus uncorrelated frailty Cox models: a comparison of different estimation procedures (2016)
  16. Jingjing Yang, Peng Ren: BFDA: A Matlab Toolbox for Bayesian Functional Data Analysis (2016) arXiv
  17. Shi, Peng; Hartman, Brian M.: Credibility in loss reserving (2016)
  18. Zhengzheng Zhang and Richard Parker and Christopher Charlton and George Leckie and William Browne: R2MLwiN: A Package to Run MLwiN from within R (2016) not zbMATH
  19. Casals, Martí; Langohr, Klaus; Carrasco, Josep Lluís; Rönnegård, Lars: Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles: a simulation study (2015)
  20. Ferreira, Guillermo; Figueroa-Zúñiga, Jorge I.; de Castro, Mário: Partially linear beta regression model with autoregressive errors (2015)

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