MAS8613 : Time Series with Advanced Topics
- Offered for Year: 2025/26
- Module Leader(s): Dr Markus Rau
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
| European Credit Transfer System | |
Aims
To gain an understanding of the principles of time series analysis. To develop skills for the modelling, analysis and forecasting of time series.
Module Summary
A time series is a set of ordered data with respect to time, such as the carbon dioxide concentration at a specific location measured at noon each day or the sales of a product recorded each month. Often in statistics, data are regarded as independent draws from a population. In time series analysis we typically do not regard consecutive observations to be independent, and build models to represent this dependence. Time series exhibit features such as trends and seasonal, or periodic, behaviour. In this module we consider modelling and inference for time series and forecasting future observations.
Outline Of Syllabus
Introduction to time series, including trend effects, seasonality and moving averages. Linear Gaussian processes, stationarity, autocovariance and autocorrelation. Autoregressive (AR), moving average (MA) and mixed (ARMA) models for stationary processes. Likelihood in a simple case such as AR(1). ARIMA processes, differencing, seasonal ARIMA as models for non-stationary processes. The role of sample autocorrelation, partial autocorrelation and correlograms in model choice. Tests of autocorrelation. Inference for model parameters. Forecasting. Dynamic linear models and the Kalman filter. Filtering and smoothing. Use of R for time series analysis. Additional advanced topics such as likelihood and least squares estimation in general ARMA models, long memory ARMA and spectral analysis and filtering will also be considered.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 2 | 1:00 | 2:00 | Revision Lectures |
| Scheduled Learning And Teaching Activities | Lecture | 20 | 1:00 | 20:00 | Formal Lectures |
| Guided Independent Study | Assessment preparation and completion | 1 | 2:00 | 2:00 | Unseen exam |
| Guided Independent Study | Assessment preparation and completion | 2 | 4:00 | 8:00 | Completion of in course assessments |
| Scheduled Learning And Teaching Activities | Lecture | 5 | 1:00 | 5:00 | Problem Classes |
| Guided Independent Study | Directed research and reading | 15 | 1:00 | 15:00 | Directed reading of advanced topic(s) |
| Scheduled Learning And Teaching Activities | Practical | 2 | 1:00 | 2:00 | Computer Practicals |
| Guided Independent Study | Independent study | 22 | 1:00 | 22:00 | Preparation time for lectures |
| Guided Independent Study | Independent study | 8 | 1:00 | 8:00 | Background reading on lectured content |
| Guided Independent Study | Independent study | 13 | 1:00 | 13:00 | Revision for unseen exam |
| Guided Independent Study | Independent study | 2 | 1:30 | 3:00 | Review of Coursework |
| Total | 100:00 |
Jointly Taught With
| Code | Title |
|---|---|
| MAS3923 | Time Series |
Teaching Rationale And Relationship
Lectures are used for the delivery of theory and explanation of methods, illustrated with examples, and for giving general feedback on marked work. Problem classes are used to help develop the students’ abilities at applying the theory to solving problems. In addition, directed research and reading of an advanced topic is used to develop the students’ ability to learn independently.
The teaching methods are appropriate to allow students to develop a wide range of skills. From understanding basic concepts and facts to higher-order thinking.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Written Examination | 120 | 2 | A | 80 | 2 hour written exam, comprising a Section A and a Section B. |
Exam Pairings
| Module Code | Module Title | Semester | Comment |
|---|---|---|---|
| Time Series | 2 | N/A |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Prob solv exercises | 2 | M | 20 | Coursework 2. Up to 6 page typeset report based upon a set assignment comprising open-ended questions. |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Prob solv exercises | 2 | M | Coursework 1. 40 minute class test, conducted during one of the timetabled one hour lecture slots. |
Assessment Rationale And Relationship
A substantial formal unseen examination is appropriate for the assessment of the material in this module. The format of the examination will enable students to reliably demonstrate their own knowledge, understanding and application of learning outcomes.
Examination problems may require a synthesis of concepts and strategies from different sections, while they may have more than one way for solution. The examination time allows the students to test different strategies, work out examples and gather evidence for deciding on an effective strategy, while carefully articulating their ideas and explicitly citing the theory they are using.
The coursework assignments allow the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback; the summative assessment has a secondary formative purpose as well as its primary summative purpose.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- MAS8613's Timetable