References in zbMATH (referenced in 44 articles )

Showing results 1 to 20 of 44.
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  1. Fasiolo, Matteo; de Melo, Flávio Eler; Maskell, Simon: Langevin incremental mixture importance sampling (2018)
  2. Selland Kleppe, Tore: Modified Cholesky Riemann manifold Hamiltonian Monte Carlo: exploiting sparsity for fast sampling of high-dimensional targets (2018)
  3. Wang, Xiaofeng; Yue, Yu Ryan; Faraway, Julian J.: Bayesian regression modeling with INLA (2018)
  4. Bob Carpenter and Andrew Gelman and Matthew Hoffman and Daniel Lee and Ben Goodrich and Michael Betancourt and Marcus Brubaker and Jiqiang Guo and Peter Li and Allen Riddell: Stan: A Probabilistic Programming Language (2017)
  5. Corani, Giorgio; Benavoli, Alessio; Demšar, Janez; Mangili, Francesca; Zaffalon, Marco: Statistical comparison of classifiers through Bayesian hierarchical modelling (2017)
  6. Culpepper, Ryan; Cobb, Andrew: Contextual equivalence for probabilistic programs with continuous random variables and scoring (2017)
  7. Dunning, Iain; Huchette, Joey; Lubin, Miles: JuMP: a modeling language for mathematical optimization (2017)
  8. Geppert, Leo N.; Ickstadt, Katja; Munteanu, Alexander; Quedenfeld, Jens; Sohler, Christian: Random projections for Bayesian regression (2017)
  9. Hilbe, Joseph M.; de Souza, Rafael S.; Ishida, Emille E. O.: Bayesian models for astrophysical data. Using R, JAGS, Python, and Stan (2017)
  10. Houpt, Joseph W.; Fifić, Mario: A hierarchical Bayesian approach to distinguishing serial and parallel processing (2017)
  11. Kühnel, Line; Sommer, Stefan; Pai, Akshay; Raket, Lars Lau: Most likely separation of intensity and warping effects in image registration (2017)
  12. Lathrop, Quinn N.; Cheng, Ying: Item cloning variation and the impact on the parameters of response models (2017)
  13. Liu, Yang; Hannig, Jan: Generalized fiducial inference for logistic graded response models (2017)
  14. Paul-Christian Buerkner: Bayesian Distributional Non-Linear Multilevel Modeling with the R Package brms (2017) arXiv
  15. Piironen, Juho; Vehtari, Aki: Comparison of Bayesian predictive methods for model selection (2017)
  16. Quentin F. Gronau, Henrik Singmann, Eric-Jan Wagenmakers: bridgesampling: An R Package for Estimating Normalizing Constants (2017) arXiv
  17. Staton, Sam: Commutative semantics for probabilistic programming (2017)
  18. Vehtari, Aki; Gelman, Andrew; Gabry, Jonah: Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC (2017)
  19. Fullerton, Andrew S.; Xu, Jun: Ordered regression models. Parallel, partial, and non-parallel alternatives (2016)
  20. Houpt, Joseph W.; MacEachern, Steven N.; Peruggia, Mario; Townsend, James T.; Van Zandt, Trisha: Semiparametric Bayesian approaches to systems factorial technology (2016)

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