MATH5805 Special Topics (Statistics)

MATH5805 is a Honours and Postgraduate Coursework course. See the course overview below.

The topic for Semester 2 2016 will be Advanced Monte Carlo Methods

Units of credit: 6

Prerequisites: Nil

Cycle of offering: Course not offered every year.

Graduate attributes: The course will enhance your research, inquiry and analytical thinking abilities.

More information: This recent course handout (pdf) contains information about course objectives, assessment, course materials and the syllabus. 

The Online Handbook entry contains information about the course. (The timetable is only up-to-date if the course is being offered this year.) 

If you are currently enrolled in MATH5805, you can log into UNSW Moodle for this course.

Course Overview

This course will cover topics in the general area of Monte Carlo methods and their application domains. The topics include Markov chain Monte Carlo and Sequential Monte Carlo methods,Quantum and Diffusion Monte Carlo techniques, as well as branching and interacting particle methodologies. The lectures cover discrete and continuous time stochastic models, starting from traditional sampling techniques (perfect simulation, Metropolis-Hasting, and Gibbs-Glauber models) to more refined methodologies such as gradient flows diffusions on constraint state space and Riemannian manifolds, ending with the more recent and rapidly developing Branching and mean field type Interacting Particle Systems techniques.