Abstract

A hierarchical vector autoregressive model is presented for analyzing differences in brain connectivity between autism spectrum disorder patients and healthy controls. This application will be used to demonstrate how probabilistic programming languages like Stan and Turing can solve quite complex applied statistical problems with state-of-the-art computational inference methodology. A brief introduction to variational inference for approximate large-scale Bayesian inference will also be given.