Examples

For beginners, we recommend to look at the following examples.

There are also examples associated with published documentation. The documentation is written for the version of Biogeme at the time of publication. The online examples are updated for the latest version.

Calculating indicators

After the parameters of a model have been estimated, the model can be used to derive various indicators, such as market shares, or elasticities, that are used by policy makers. This is explained in details in Bierlaire (2018a)

Calculating indicators with Biogeme

Timing function evaluation

Provides some timing information about the calculation of the log likelihood function of some mpdels.

Monte-Carlo integration

It is possible to calculate complex integrals using Monte-Carlo integration in Biogeme. This is explained in details in Bierlaire (2019)

Monte-Carlo integration with Biogeme

Choice models with latent variables

Hybrid choice models, that is, choice models involving latent variables, can be estimated with Biogeme. This is explained in details in Bierlaire (2018b)

Assisted specification algorithm

An assisted specification algorithm is available in Biogeme. Its usage is detailed in Bierlaire and Ortelli (2023)

Assisted specification with Biogeme

Estimation with samples of alternatives

It is possible to estimate choice models using only a sample of alternatives. The implementation is still experimental, and continues to be test. It is described in Bierlaire and Paschalidis (2023)

Sampling of alternatives

Multiple Discrete Continuous Extreme Value models

It is possible to estimate the parameters of Multiple Discrete Continuous Extreme Value (MDCEV) models with Biogeme, and to use the estimated model for forecasting. This is described in n upcoming report.