Demos
DemosΒΆ
Use the menu on the left to navigate through the different demos.
A brief description of each demo is provided below:
Mixed logit with simulated data - A simple demo using artificial panel choice data from 500 respondents on 5 different choice situations (menus)
Mixed logit with Toyota data - This demo shows how to apply a mixed logit model to the Toyota dataset that was made available by Kenneth Train at https://eml.berkeley.edu/~train/ec244ps.html
Amortized variational inference - This demo showcases the scalability of PyDCML by considering an artificial dataset containing panel data from 10000 respondents on 10 different choice situations (menus)