References in zbMATH (referenced in 38 articles )

Showing results 1 to 20 of 38.
Sorted by year (citations)

1 2 next

  1. Culpepper, Ryan; Cobb, Andrew: Contextual equivalence for probabilistic programs with continuous random variables and scoring (2017)
  2. Dunning, Iain; Huchette, Joey; Lubin, Miles: JuMP: a modeling language for mathematical optimization (2017)
  3. Geppert, Leo N.; Ickstadt, Katja; Munteanu, Alexander; Quedenfeld, Jens; Sohler, Christian: Random projections for Bayesian regression (2017)
  4. Hilbe, Joseph M.; de Souza, Rafael S.; Ishida, Emille E. O.: Bayesian models for astrophysical data. Using R, JAGS, Python, and Stan (2017)
  5. Houpt, Joseph W.; Fifić, Mario: A hierarchical Bayesian approach to distinguishing serial and parallel processing (2017)
  6. Kühnel, Line; Sommer, Stefan; Pai, Akshay; Raket, Lars Lau: Most likely separation of intensity and warping effects in image registration (2017)
  7. Lathrop, Quinn N.; Cheng, Ying: Item cloning variation and the impact on the parameters of response models (2017)
  8. Liu, Yang; Hannig, Jan: Generalized fiducial inference for logistic graded response models (2017)
  9. Paul-Christian Buerkner: Bayesian Distributional Non-Linear Multilevel Modeling with the R Package brms (2017) arXiv
  10. Piironen, Juho; Vehtari, Aki: Comparison of Bayesian predictive methods for model selection (2017)
  11. Quentin F. Gronau, Henrik Singmann, Eric-Jan Wagenmakers: bridgesampling: An R Package for Estimating Normalizing Constants (2017) arXiv
  12. Staton, Sam: Commutative semantics for probabilistic programming (2017)
  13. Vehtari, Aki; Gelman, Andrew; Gabry, Jonah: Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC (2017)
  14. Fullerton, Andrew S.; Xu, Jun: Ordered regression models. Parallel, partial, and non-parallel alternatives (2016)
  15. Houpt, Joseph W.; MacEachern, Steven N.; Peruggia, Mario; Townsend, James T.; Van Zandt, Trisha: Semiparametric Bayesian approaches to systems factorial technology (2016)
  16. Katahira, Kentaro: How hierarchical models improve point estimates of model parameters at the individual level (2016)
  17. Lee, Cathy Yuen Yi; Wand, Matt P.: Streamlined mean field variational Bayes for longitudinal and multilevel data analysis (2016)
  18. Luttinen, Jaakko: BayesPy: variational Bayesian inference in Python (2016)
  19. Philipp H Boersch-Supan, Leah R Johnson: deBInfer: Bayesian inference for dynamical models of biological systems in R (2016) arXiv
  20. Shiffrin, Richard M.; Chandramouli, Suyog H.; Grünwald, Peter D.: Bayes factors, relations to minimum description length, and overlapping model classes (2016)

1 2 next