Time: 1:15pm - 5pm
Date: June 19, 2017
Venue: Fred Gruen Seminar Room, Level 1, H.W. Arndt Building (Building 25A), Australian National University
Registration: Please register here and bring along a personal laptop!
In this afternoon workshop, participants will be given an introduction to the Stan modeling language.
Stan is a flexible modeling language capable of performing efficient Bayesian inference on any model with a continuous parameter space for which we can evaluate a (log) likelihood. It implements a cutting-edge variety of Hamiltonian Monte Carlo, which will happily work with tens of thousands of parameters, and often produces reliable estimates with only a few hundred iterations. It is currently possible to call Stan from within R, Python, Julia, Mathematica, MATLAB, Stata, or at the command line.
Participants should have R, R Studio and Stan installed (we will only use R to run and evaluate models; participants needn’t be proficient in R).
About the instructor:
Jim Savage is an applied modeler and Data Science Lead at frontier markets lender Lendable in New York City. Previously he was at the Grattan Institute, La Trobe University, and the Australian Treasury. With Andrew Gelman, Shoshana Vasserman and David Stephan, he is currently writing a book on Bayesian Econometrics in Stan.