MTH4230 Time series and random processes in linear systems
Faculty of Science
MTH4230 Time series and random processes in linear systems is a level 4, 6-credit-point, undergraduate and postgraduate unit from the Faculty of Science, offered in 2025 in Semester 2 at Clayton. It has no prerequisites.
- Credit points
- 6
- Offered in 2025
- Semester 2
- Clayton
- Assessment
- Exam 50%
- and 1 other task
This is the 2025 handbook entry. See the 2027 entry.
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Requisites
Before MTH4230
No prerequisites or corequisites besides the enrolment rules below.
After MTH4230
No unit lists MTH4230 as a prerequisite in the 2025 handbook.
Enrolment rules
You must be enrolled in the Graduate Certificate in Mathematics or the Master of Mathematics
Prohibition: MTH3230
Overview
Multivariate distributions. Estimation: maximum of likelihood and method of moments. Confidence intervals. Analysis in the time domain: stationary models, autocorrelation, partial autocorrelation. ARMA and ARIMA models. Analysis in the frequency domain (Spectral analysis): spectrum, periodigram, linear and digital filters, cross-correlations and cross-spectrum, spectral estimators, confidence interval for the spectral density. State-space models. Kalman filter. Empirical Orthogonal Functions and other Eigen Methods. Use of ITSM.
Offerings in 2025
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | On campus |
Assessment
- Continuous assessmentDemonstration50%
- Final assessment - Exam (3 hours and 10 minutes)Examination50%
Learning outcomes
When you finish this unit, you should be able to:
- 1
Critically evaluate and articulate the concept of stationary time series.
- 2
Demonstrate an in-depth understanding of the concept of projection and its use in forecasting.
- 3
Analyse and synthesise models of autoregression, moving averages, and their combinations.
- 4
Perform advanced analysis of time series in both time domain and frequency domain.
- 5
Apply the Kalman filter to random systems, demonstrating proficiency in both theoretical understanding and practical implementation.
- 6
Conduct analysis of time series data using the ITSM package, showcasing the ability to handle complex datasets and derive meaningful insights
Workload and teaching
- Applied sessions22 hours
- Seminars36 hours
- Teaching approachActive learning
Three 1-hour seminars;
One 2-hour applied class (in weeks 2-12) and
7 hours of independent study per week.
Active learning will occur in lectures and applied classes.
Contacts
- Unit Coordinators
- Associate Professor Tianhai Tian
- Chief Examiners
- Associate Professor Tianhai Tian
Common questions
What are the prerequisites for MTH4230?
MTH4230 has no prerequisites, but enrolment rules apply.
When is MTH4230 offered?
In 2025, MTH4230 runs in Semester 2 at Clayton.
Does MTH4230 have an exam?
Yes. The exam is worth 50% of the final mark, alongside 1 other task.