# Documents

Various documents describing the usage of Biogeme are available here in PDF format:

- PythonBiogeme: a short introduction [PDF]
- Calculating indicators with PythonBiogeme [PDF]
- Monte-Carlo integration with PythonBiogeme [PDF]
- Estimating choice models with latent variables with PythonBiogeme [PDF]
- BisonBiogeme: estimating a first model [PDF]
- BisonBiogeme: syntax od the modeling language [PDF]

An online documentation of the Python files in the Biogeme distribution is available. It has ben automatically extracted from the files themselves using Doxygen, for the sake of consistency.

In this document, we present step by step how to specify a simple model, estimate its parameters and interpret the output of the software package. We assume that the reader is already familiar with discrete choice models, and has successfully installed Python Biogeme. This document has been written using Python Biogeme 2.5, but should remain valid for future versions.

Reference: Bierlaire (2016) PythonBiogeme: a short introduction, Technical report TRANSP-OR 160706. Transport and Mobility Laboratory, ENAC, EPFL.

In this document, we describe how PythonBiogeme can be used to apply a model. It is shown how to calculate market shares, elasticities and willingness ot pay. This document has been written using Python Biogeme 2.6, but should remain valid for future versions. The model files used in this document are available here.

Reference: Bierlaire (2017) Calculating indicators with PythonBiogeme, Technical report TRANSP-OR 170517. Transport and Mobility Laboratory, ENAC, EPFL.

In this document, we investigate some aspects related to Monte-Carlo integration, which is particularly useful when estimating mixtures choice models, as well as choice models with latent variables. We assume that the reader is already familiar with discrete choice models, with PythonBiogeme, and with simulation methods, although a short summary is provided. This document has been written using PythonBiogeme 2.4, but should remain valid for future versions.

Reference: Bierlaire (2015), Monte-Carlo integration with PythonBiogeme, Technical report TRANSP-OR 150806. Transport and Mobility Laboratory, ENAC, EPFL.

In this document, we present how to estimate choice models involving latent variables. We assume that the reader is already familiar with discrete choice models, with latent variables, and with PythonBiogeme. This document has been written using PythonBiogeme 2.5, but should remain valid for future versions.

Reference: Bierlaire (2016), Estimating choice models with latent variables with PythonBiogeme, Technical report TRANSP-OR 160628. Transport and Mobility Laboratory, ENAC, EPFL.

In this document, we present step by step how to specify a simple model, estimate its parameters and interpret the output of the software package. We assume that the reader is already familiar with discrete choice models, and has successfully installed Bison Biogeme. This document has been written using Bison Biogeme 2.4, but should be valid for future versions, as no major release if foreseen.

Reference: Bierlaire (2015) BisonBiogeme: estimating a first model, Technical report TRANSP-OR 150720. Transport and Mobility Laboratory, ENAC, EPFL.

In this document, we present the syntax of the modeling language of BisonBiogeme. This document is designed to be a reference. We strongly encourage the reader to first consult the primer, where the syntax of a first model is analyzed in details, as well as the many examples provided online. This document has been written using BisonBiogeme 2.4, but should be valid for future versions, as no major release if foreseen.

Reference: Bierlaire (2015) BisonBiogeme: syntax of the modeling language, Technical report TRANSP-OR 151102. Transport and Mobility Laboratory, ENAC, EPFL.