37262 Simulation Modelling6cp; Forms of attendance in this subject have changed to enable social distancing and reduce the risks of spreading COVID-19 in our community. There may also have been changes to the assessment requirements. Consequently, the Subject Outline information for this subject has changed. Details of the changes may be published in an Addendum to the Subject Outline which is available through your LMS (Blackboard or Canvas).
Requisite(s): 37161 Probability and Random Variables
These requisites may not apply to students in certain courses. See access conditions.
Anti-requisite(s): 35363 Stochastic Models
There are many circumstances where it is impractical or impossible to analytically derive a solution to a problem. In these cases, simulation provides a way to gain insight without derivations. This subject considers the generation of random variables and their use to simulate random processes including Poisson processes, random walks and queuing systems, perform numerical integration, and solve difference equations. The methods of simulation considered include acceptance–rejection, importance sampling, Monte Carlo, and the Metropolis-Hastings algorithm.
Detailed subject description.