References in zbMATH (referenced in 62 articles )

Showing results 1 to 20 of 62.
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  1. Cepeda-Cuervo, Edilberto; Jaimes, Daniel; Marín, Margarita; Rojas, Javier: Bayesian beta regression with Bayesianbetareg R-package (2016)
  2. Farias, Rafael B.A.; Montoril, Michel H.; Andrade, José A.A.: Bayesian inference for extreme quantiles of heavy tailed distributions (2016)
  3. Hernández-Lobato, José Miguel; Gelbart, Michael A.; Adams, Ryan P.; Hoffman, Matthew W.; Ghahramani, Zoubin: A general framework for constrained Bayesian optimization using information-based search (2016)
  4. Turner, Brandon M.; Sederberg, Per B.; McClelland, James L.: Bayesian analysis of simulation-based models (2016)
  5. Velasco-Cruz, Ciro; Contreras-Cruz, Luis Fernando; Smith, Eric P.; Rodríguez, José E.: A varying coefficients model for estimating finite population totals: a hierarchical Bayesian approach (2016)
  6. White, Arthur; Wyse, Jason; Murphy, Thomas Brendan: Bayesian variable selection for latent class analysis using a collapsed Gibbs sampler (2016)
  7. Baumgartner, Carolin; Gruber, Lutz F.; Czado, Claudia: Bayesian total loss estimation using shared random effects (2015)
  8. Lin, Xiaoyan; Cai, Bo; Wang, Lianming; Zhang, Zhigang: A Bayesian proportional hazards model for general interval-censored data (2015)
  9. Liu, Fangfang; Wang, Chong; Liu, Peng: A semi-parametric Bayesian approach for differential expression analysis of RNA-seq data (2015)
  10. Mostafa, Ayman A.: Bayesian analysis technique for generalized Cox’s proportional hazards model using BUGS: applications in medical data (2015)
  11. Müller, Peter; Quintana, Fernando Andrés; Jara, Alejandro; Hanson, Tim: Bayesian nonparametric data analysis (2015)
  12. Pérez-Elizalde, Sergio; Cuevas, Jaime; Pérez-Rodríguez, Paulino; Crossa, José: Selection of the bandwidth parameter in a Bayesian kernel regression model for genomic-enabled prediction (2015)
  13. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2015)
  14. Tempelman, Robert J.: Statistical and computational challenges in whole genome prediction and genome-wide association analyses for plant and animal breeding (2015)
  15. Wood, Simon N.: Core statistics (2015)
  16. Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi: Bayesian exploratory factor analysis (2014)
  17. Handcock, Mark S.; Gile, Krista J.; Mar, Corinne M.: Estimating hidden population size using respondent-driven sampling data (2014)
  18. Kirschenmann, Thomas; Popova, Elmira; Damien, Paul; Hanson, Tim: Decision dependent stochastic processes (2014)
  19. Shang, Han Lin: Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density (2014)
  20. Ahn, Jaeil; Mukherjee, Bhramar; Gruber, Stephen B.; Ghosh, Malay: Bayesian semiparametric analysis for two-phase studies of gene-environment interaction (2013)

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