Transport Demand Modelling Course

This repository intends to gather, and make available, the supporting materials for the Transport Demand Modelling course, lectured by Prof. Filipe Moura.
This material is also an open source tutorial for applying R programming (chapters 1-7 and 9) and Python Biogeme (chapter 8) in transport demand modelling.

Summary

1. Exploratory Data Analysis

2. Multiple Linear Regression models

3. Exploratory Factor Analysis

4. Cluster Analysis

5. Generalized linear models

6. Spatial regression models

7. Panel Data Models

8. Discrete Choice Models

   • Multinomial
   • Nested
   • Ordered Models

9. Hazard-Based Duration Models

Files

• In the Data folder you may find all the files for the exercises.
• The Code folder contains scripts for each topic.

Slides

You may find all lectures slides in the course page.

R and Python stuff

• How to install R and RStudio
• Check some tips how to make your home assignments as static or dynamic outputs with R Markdown.
• How to install Python and Pandas Biogeme

Acknowledgements:

• Gabriel Valença: preparation of code of Chapters 1-5, 7.
• Rosa Félix: preparation of code of Chapter 6, "How to install R", "Tips for RMarkdown", revision of code of Chapters 1-7, 9.
• Miguel Costa: preparation of code of Chapter 8, and "How to install Python".
• Carlos Roque: preparation of code of Chapter 9.
• Filipe Moura: supervision.

Reference

If you use this material, please cite as:

Filipe Moura, Gabriel Valença, Miguel Costa, Carlos Roque, & Rosa Félix. (2021, March). U-Shift/Transport-Demand-Modelling: Supporting materials to Transportation Demand Modelling classes at Instituto Superior Técnico - University of Lisbon. (Version 2021.0). GitHub. http://doi.org/10.5281/zenodo.4599525