NOTE: This repo has been moved to be a part of Transport Demand Modelling.
This chapter explores how to estimate and analyze Discrete Choice Models, their uses and applications.
- Understand Biogeme concepts
- Understand possible applications for Biogeme
- Be able to create discrete choice models
- Learn some tools that can be used to create more complicated models in the future
- Learn some handy tricks/tools/packages
Biogeme is a open source Python package designed for the maximum likelihood estimation of parametric models in general, with a special emphasis on discrete choice models.
| File | Topic | Description |
|---|---|---|
| 01-biogeme-basics.ipynb | Logit Basics | How to estimate a simple multinomial logit model. |
| 02-logit-estimators-results.ipynb | Goodness of fit | How to analyze the models goodness of fit indicators. |
| 03-logit-validation.ipynb | Cross-validation | How to perform cross-validation on a dataset using a logit model. |
| 04-logit-train-test.ipynb | Prediction | How to split a dataset into train and test dataset to perform prediction. Evaluate results on a confusion matrix. |
| 05-probit-basics.ipynb | Probit | How to train a binomial probit model. |
| File | Topic | Description |
|---|---|---|
| 01-logit-nested.ipynb | Nested Logit Basics | How to estimate a simple nested logit model. |
| 02-logit-nested-market.ipynb | Market Share | How to compute market shares of alternatives. |
| 03-logit-nested-revenue-scenarios.ipynb | Market Share Scenarios | How to create scenarios and compute their market share outcomes. |
| 04-logit-nested-elasticities.ipynb | Elasticities | How to compute elasticities. |
| 05-logit-nested-WTP.ipynb | Willingness To Pay (WTP) | How to compute willingness to pay indicators. |
| File | Topic | Description |
|---|---|---|
| 01-biogeme-ordered.ipynb | Ordered Logit Basics | How to estimate a simple ordered logit model. |
- Installation: https://biogeme.epfl.ch/install.html
- Datasets: https://biogeme.epfl.ch/data.html
- Documentation: https://biogeme.epfl.ch/documents.html
- Code Documentation: https://biogeme.epfl.ch/sphinx/index.html
- Examples: https://biogeme.epfl.ch/examples.html
- Google Groups Forum: https://groups.google.com/forum/#!forum/biogeme