The module webpage can be found here.
Lecturer: Susana Gomes
Teaching Assistant: Kamran Pentland
- Simply download (or clone) the repository to a new folder in on your laptop.
- Fire up any of the notebooks using Jupyter notebook.
Notebooks will be uploaded before each support class. If something is not working, get in contact with me.
Support Class 1.ipynb
- Basic commands
- Linear algebra basics
- Simple random walk exercises
Support Class 2.ipynb
- Sheet 1 simulations
- Q3(c): Three state Markov chain
- Q4(c): Wright-Fisher model
Support Class 3.ipynb
- Sheet 2 simulations
- Q1(c/d): DTMC simulation (e'vals/e'vectors/stationary distributions)
- Q2(d): geometric random walk
Support Class 4.ipynb
- Sheet 3 simulations
- Q2: CTMC simulation
- Q3: playing with multivariate Gaussians
- Q4: Geometric Brownian Motion SDE
- Q5: Fractional Brownian motion/Brownian Bridges/Gaussian Processes
Support Class 5.ipynb
- Sheet 4 simulations
- Q2: Contact process simulation (with Gillespie algorithm)
Support Class 6.ipynb
- Sheet 5 simulations
- Q2: Using the 'networkx' package to simulate random networks
This will be updated as the module progresses.
It's recommended you use Overleaf (particularly useful for group projects as multiple people can work on the same document at the same time). You can sign up with your Warwick details (and you should have access to premium features): https://www.overleaf.com/
- Log Normal Distribution: https://en.wikipedia.org/wiki/Log-normal_distribution
- Log Normal Scipy Documentstion: https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.lognorm.html
- KDE plot visualisation: https://mathisonian.github.io/kde/
- Fokker-Planck Equation: book Stochastic Processes in physics and chemistry - N.G. Van Kampen
- Ornstein-Uhlenbeck process: https://en.wikipedia.org/wiki/Ornstein%E2%80%93Uhlenbeck_process#Fokker%E2%80%93Planck_equation_representation
- Colour options in matplotlib https://xkcd.com/color/rgb/