boa

BOA is an R/S-PLUS program for carrying out convergence diagnostics and statistical and graphical analysis of Monte Carlo sampling output. It can be used as an output processor for the BUGS software or for any other program which produces sampling output.

Keywords for this software

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References in zbMATH (referenced in 69 articles , 1 standard article )

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  1. Richardson, Robert; Kottas, Athanasios; Sansó, Bruno: Bayesian non-parametric modeling for integro-difference equations (2018)
  2. Richardson, Robert; Kottas, Athanasios; Sansó, Bruno: Flexible integro-difference equation modeling for spatio-temporal data (2017)
  3. De la Cruz, Rolando; Meza, Cristian; Arribas-Gil, Ana; Carroll, Raymond J.: Bayesian regression analysis of data with random effects covariates from nonlinear longitudinal measurements (2016)
  4. Volos, Christos K. (ed.); Vaidyanathan, Sundarapandian (ed.); Pham, Viet-Thanh (ed.); Tlelo-Cuautle, Esteban (ed.): Discrete chaotic dynamics for economics and social science (2016)
  5. Xavier Fernández-i-Marín: ggmcmc: Analysis of MCMC Samples and Bayesian Inference (2016) not zbMATH
  6. Fellingham, Gilbert W.; Kottas, Athanasios; Hartman, Brian M.: Bayesian nonparametric predictive modeling of group health claims (2015)
  7. González, Jorge; Barrientos, Andrés F.; Quintana, Fernando A.: Bayesian nonparametric estimation of test equating functions with covariates (2015)
  8. Mostafa, Ayman A.: Bayesian analysis technique for generalized Cox’s proportional hazards model using BUGS: applications in medical data (2015)
  9. Müller, Peter; Quintana, Fernando Andrés; Jara, Alejandro; Hanson, Tim: Bayesian nonparametric data analysis (2015)
  10. Naranjo, L.; Pérez, C. J.; Martín, J.: Bayesian analysis of some models that use the asymmetric exponential power distribution (2015)
  11. Torabi, Mahmoud; Shokoohi, Farhad: Non-parametric generalized linear mixed models in small area estimation (2015)
  12. Romeo, Jose S.; Meyer, Renate; Reyes-Lopez, Felipe E.: Hierarchical failure time regression using mixtures for classification of the immune response of atlantic salmon (2014)
  13. Baghfalaki, Taban; Ganjali, Mojtaba; Berridge, Damon: Robust joint modeling of longitudinal measurements and time to event data using normal/independent distributions: A Bayesian approach (2013)
  14. Leen Slaets; Gerda Claeskens; Bernard Silverman: Warping Functional Data in R and C via a Bayesian Multiresolution Approach (2013) not zbMATH
  15. Paulino, Carlos Daniel; Silva, Giovani L.; Branco, Márcia: A fully Bayesian parametric approach for cytogenetic dosimetry (2013)
  16. Deborah Burr: bspmma: An R Package for Bayesian Semiparametric Models for Meta-Analysis (2012) not zbMATH
  17. Hong, Zhaoping; Lian, Heng: BOPA: A Bayesian hierarchical model for outlier expression detection (2012)
  18. Ji, Yonggang; Lin, Nan; Zhang, Baoxue: Model selection in binary and Tobit quantile regression using the Gibbs sampler (2012)
  19. Tojeiro, Cynthia A. V.; Louzada, Francisco: A general threshold stress hybrid hazard model for lifetime data (2012)
  20. Torabi, Mahmoud: Hierarchical Bayes estimation of spatial statistics for rates (2012)

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