Stan

Stan: A C++ Library for Probability and Sampling. Stan is a probabilistic programming language implementing full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized maximum likelihood estimation with Optimization (BFGS). Stan is coded in C++ and runs on all major platforms.

Keywords for this software

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References in zbMATH (referenced in 16 articles )

Showing results 1 to 16 of 16.
Sorted by year (citations)

  1. Geppert, Leo N.; Ickstadt, Katja; Munteanu, Alexander; Quedenfeld, Jens; Sohler, Christian: Random projections for Bayesian regression (2017)
  2. Lathrop, Quinn N.; Cheng, Ying: Item cloning variation and the impact on the parameters of response models (2017)
  3. Fullerton, Andrew S.; Xu, Jun: Ordered regression models. Parallel, partial, and non-parallel alternatives (2016)
  4. Houpt, Joseph W.; MacEachern, Steven N.; Peruggia, Mario; Townsend, James T.; Van Zandt, Trisha: Semiparametric Bayesian approaches to systems factorial technology (2016)
  5. Katahira, Kentaro: How hierarchical models improve point estimates of model parameters at the individual level (2016)
  6. Luttinen, Jaakko: BayesPy: variational Bayesian inference in Python (2016)
  7. Philipp H Boersch-Supan, Leah R Johnson: deBInfer: Bayesian inference for dynamical models of biological systems in R (2016) arXiv
  8. Shiffrin, Richard M.; Chandramouli, Suyog H.; Grünwald, Peter D.: Bayes factors, relations to minimum description length, and overlapping model classes (2016)
  9. Green, Peter J.; Łatuszyński, Krzysztof; Pereyra, Marcelo; Robert, Christian P.: Bayesian computation: a summary of the current state, and samples backwards and forwards (2015)
  10. Niemi, Jarad; Mittman, Eric; Landau, Will; Nettleton, Dan: Empirical Bayes analysis of RNA-seq data for detection of gene expression heterosis (2015)
  11. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2015)
  12. Vincent, Benjamin T.: A tutorial on Bayesian models of perception (2015)
  13. Adrien Todeschini, Francois Caron, Marc Fuentes, Pierrick Legrand, Pierre Del Moral: Biips: Software for Bayesian Inference with Interacting Particle Systems (2014) arXiv
  14. Kruschke, John: Doing Bayesian data analysis. A tutorial introduction with R, JAGS, and Stan (2014)
  15. Vandekerckhove, Joachim: A cognitive latent variable model for the simultaneous analysis of behavioral and personality data (2014)
  16. Lawrence M. Murray: Bayesian State-Space Modelling on High-Performance Hardware Using LibBi (2013) arXiv