Here, you will find tutorials. Tutorials aim to explain concepts that are important to choice modelling. They are extensions of the lecture materials and lab sessions, providing a deeper understanding of the topics covered. They do not contain any exercises. The current list of topics is:
- Tutorial 0: Debugging common error messages and issues in Python, Pandas and Biogeme (new)
- Tutorial 1: The data generating process and bias
- Tutorial 2: The loglikelihood function
- Tutorial 3: The concave likelihood function of the linear-additive RUM-MNL model
- Tutorial 4: Local versus global maxima
- Tutorial 5: The impact of ignoring the panel structure of choice data
- Tutorial 6: The expected maximum utility and the LogSum formula
The tutorials are written in Jupyter notebooks. It is highly recommended that you download the notebooks and run them on your own computer. Some notebooks contain interactive graphs that are not displayed on GitHub. You are also encouraged to "play" with the code yourself (e.g. to test whether you really understood the topic).
The list of tutorials may be further extended in the future.