Good software tools are essential for effective data analysis. In this talk, Bob will introduce Stan, a probabilistic programming language for expressing statistical models. It implements Bayesian inference (via MCMC sampling) and penalised maximum likelihood estimation (via optimisation). Stan is similar to BUGS, but more general, scalable and efficient. It is provided as open-source software, with interfaces to other widely used languages (including R, Python and MATLAB). Over 100 papers have already been published using Stan across the biological, physical and social sciences.
Bob will present a brief overview of Stan and how it works, followed by a few case studies and examples of problems for which Stan is ideally suited.
More information on Stan is available at: mc-stan.org/