Lecturer: Professor Michael Pitt: click here for his bio.
Tutorials: Tuesdays 5pm-6pm in S3.05 (sorry it's the late shift!)
This document covers all key topics that you should learn from the course.
It may not be fully comprehensive of the course - if you would like to see any points added, please let me know.
There may be some typos - sorry! Again, please let me know if you see any.
Tutorial 1:
A brief comparison between Weak and Strict stationarity
Tutorial 2:
Tutorial 3:
Tutorial 4:
Note: Best Linear Predictor <==> Prediction errors orthogonal to prediction variables.
Comes from projection theorem of Hilbert Spaces
See here for more details
Tutorial 5:
Tutorial 6:
Tutorial 7:
(Graphic in worksheet has been taken from http://gnuplot.sourceforge.net/demo_4.4/random.html and edited)Bonus Tutorial:
Kolmogrov Smirnov + Kalman Smoother:
2018 Mock Exam:
If you have any questions about course content or tutorial questions leading up to the exam, feel free to drop me an email.
Extra Reading:
Here is a PhD thesis submitted by Dr. Nawa Raj Pokhrel in 2018 titled "Statistical Analysis and Modeling of Cyber Security and Health Sciences ". If you want to see the application of different time series models to forecast the number of OS vulnerabilities in Windows 7, OS X and Linux, have a read of Chapter 3. The paper is attached here.
Those who are interested in probability theory and real analysis can see an interesting paper by Ioannis Kasparis (2016) which uses results from Metric Spaces and Probability Theory to prove invertibility of the lag operator here.