Automatic Code Generation for Statistical Models with Augmentation and Collapsing

This thesis presents a system for automatically generating code for a set of Bayesian statistical models. The overall contributions include a system for performing pattern matching and symbolic computations, a schema system of efficiently managing statistical operations in a reusable manner. Additionally, the overall system for generating efficient code is also presented, alongside the general architecture that enables this process.