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.
School of Mathematical Sciences
- Second semester 2017 (Day)
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.
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.
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.
Three 1-hour lectures and one 2-hour support class per week
See also Unit timetable information