Course co-ordinator(s): Dr Fraser Daly (Edinburgh).
Aims:
This course aims to provide a good understanding of the concepts and methods used in time series analysis and advanced techniques for data analytics.
Detailed Information
Course Description: Link to Official Course Descriptor.
Pre-requisites: none.
Location: Edinburgh.
Semester: 2.
Syllabus:
• Basic time series concepts and operators
• Stationary processes, general linear filter, autocorrelation function and spectrum
• MA, AR and ARMA processes
• ARIMA processes and Random Walk (RW) with or without drift
• Model estimation and model selection
• Models with trend and/or seasonality
• Forecasting
• Introduction to nonlinear processes
• Elementary principles of machine learning
• Copulas
• Extreme value theory
SCQF Level: 11.
Credits: 15.
Other Information
Help: If you have any problems or questions regarding the course, you are encouraged to contact the course leader.
Canvas: further information and course materials are available on Canvas