Course overview
The course aims to equip students with the modern tools of a statistician for intensive computing in the Bayesian or variational approaches. Students will learn to implement and tune a variety of MCMC samplers and algorithms for inference in complex problems.
- Foundations of Inference and Simulation
- Markov Chain Monte Carlo
- Further Topics
Course learning outcomes
- Describe and implement statistical algorithms to perform inference in a complex statistical problem
- Interpret output and critically appraise algorithm performance
- Choose and justify suitable approaches to model problems
Availability
Class details
Adelaide City Campus East
Class number 50723
Section FR01
Size 50
Available 50
Class number 50724
Section PR01
Size 25
Available 25
Class number 50725
Section PR02
Size 25
Available 25
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