MTH3230 · Monash University
Time series and random processes in linear systems
- Credit points
- 6
- Level
- 3
- Workload
- —
- Faculty
- Science
What it covers
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.
Assessment
| Task | Type | Weight |
|---|---|---|
| Final assessment - Exam (3 hours and 10 minutes) | Examination | 50% |
| Continuous assessment | Demonstration | 50% |
When and where
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | On-campus |