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
References in zbMATH (referenced in 11 articles )
Showing results 1 to 11 of 11.
- Fullerton, Andrew S.; Xu, Jun: Ordered regression models. Parallel, partial, and non-parallel alternatives (2016)
- Houpt, Joseph W.; MacEachern, Steven N.; Peruggia, Mario; Townsend, James T.; Van Zandt, Trisha: Semiparametric Bayesian approaches to systems factorial technology (2016)
- Katahira, Kentaro: How hierarchical models improve point estimates of model parameters at the individual level (2016)
- Luttinen, Jaakko: BayesPy: variational Bayesian inference in Python (2016)
- Shiffrin, Richard M.; Chandramouli, Suyog H.; Grünwald, Peter D.: Bayes factors, relations to minimum description length, and overlapping model classes (2016)
- Green, Peter J.; Łatuszyński, Krzysztof; Pereyra, Marcelo; Robert, Christian P.: Bayesian computation: a summary of the current state, and samples backwards and forwards (2015)
- Niemi, Jarad; Mittman, Eric; Landau, Will; Nettleton, Dan: Empirical Bayes analysis of RNA-seq data for detection of gene expression heterosis (2015)
- Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2015)
- Vincent, Benjamin T.: A tutorial on Bayesian models of perception (2015)
- Kruschke, John: Doing Bayesian data analysis. A tutorial introduction with R, JAGS, and Stan (2014)
- Vandekerckhove, Joachim: A cognitive latent variable model for the simultaneous analysis of behavioral and personality data (2014)