Statistics and Data Analysis
This 1 day DISCnet event, given by Jonathan Loveday (Sussex), will cover two aspects of Bayesian model fitting: Bayesian Hierarchical Models (BHM) and Approximate Bayesian Computation (ABC). The course runs on 1 April at Queen Mary University of London.
To acquire the skills needed for analysis of experimental data and model fitting.
At the end of this course, a successful student will be able to:
Fit Bayesian hierarchical models to data, allowing marginalisation over unknown nuisance parameters
Use approximate Bayesian computation to allow for likelihood-free inference
Examples will be given during the course.
Prerequisites / Linked Modules
It is recommended that students have the following software installed on their laptops:
Anaconda python distribution (https://www.anaconda.com/download/)
emcee, affine-invariant MCMC code (http://dfm.io/emcee/current/)
1030 Arrival Coffee
1100 Intro to Bayesian Hierarchical Modelling and Approximate Bayesian Computation
1330 Practical exercises