6 points, SCA Band 2, 0.125 EFTSL
Undergraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Faculty
Organisational Unit
School of Mathematical Sciences
Chief examiner(s)
Associate Professor Tianhai Tian
Coordinator(s)
Associate Professor Tianhai Tian
Unit guides
Synopsis
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.
Outcomes
On completion of this unit students will be able to:
- Articulate the concept of stationary time series;
- Manipulate the concept of projection and its use in forecasting;
- Understand the models of autoregression and moving averages and their combinations;
- Analyse time series in time domain as well as frequency domain;
- Apply the Kalman filter to random systems;
- Analyse time series data using the ITSM package.
Assessment
Examination (3 hours): 60% (Hurdle)
Continuous assessment: 40%
Hurdle requirement: To pass this unit a student must achieve at least 50% overall and at least 40% for the end-of-semester exam.
Workload requirements
Three 1-hour lectures and one 2-hour support class per week
See also Unit timetable information