Coursebooks

Mathematical modelling of behavior

Bierlaire Michel

English

Summary

Discrete choice models allow for the analysis and prediction of individuals' choice behavior. The objective of the course is to introduce both methodological and applied aspects, in the field of marketing, transportation, and finance.

Content

MOOC

1. Introduction and examples

2. Choice theory

3. Binary choice

4. Multinomial choice

5. Specification testing

6. Prediction

Ex cathedra lectures

7. Nested Logit model

8. Multivariate extreme Value models

9. Sampling

10. Mixed models.

11. Choice models with latent variables.

Learning Outcomes

By the end of the course, the student must be able to:
• Model discrete choice

Transversal skills

• Use a work methodology appropriate to the task.
• Assess one's own level of skill acquisition, and plan their on-going learning goals.
• Use both general and domain specific IT resources and tools

Teaching methods

Lectures:

The first half of the semester is based on the online MOOC "Introduction to discrete choice models". There is no lecture in class.

The second half of the semester is based on ex-cathedra lectures in class.

Exercices and laboratories:

They are organized every week during the semester. The students will estimate the parameters of behavioral models based on real data.

Expected student activities

Every week, the students are supposed to

1. read the appropriate material, according to the schedule (the material for a given week is supposed to be read before the lecture of that week);
2. work on the assignments for the laboratories.

Assessment methods

Written

Dans le cas de l¿art. 3 al. 5 du Règlement de section, l¿enseignant décide de la forme de l¿examen qu¿il communique aux étudiants concernés.

Resources

Bibliography

Ben-Akiva and Lerman (1985) Discrete Choice Analysis, MIT Press.Train (2003) Discrete Choice Methods with Simulation, Cambridge University Press.

In the programs

• Mathematics - master program, 2019-2020, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Mathematics - master program, 2019-2020, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Applied Mathematics, 2019-2020, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Applied Mathematics, 2019-2020, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Computational science and Engineering, 2019-2020, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Computational science and Engineering, 2019-2020, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Energy Management and Sustainability, 2019-2020, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Energy Management and Sustainability, 2019-2020, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Financial engineering, 2019-2020, Master semester 1
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks
• Financial engineering, 2019-2020, Master semester 3
• Semester
Fall
• Exam form
Written
• Credits
5
• Subject examined
Mathematical modelling of behavior
• Lecture
2 Hour(s) per week x 14 weeks
• Exercises
2 Hour(s) per week x 14 weeks

MoTuWeThFr
8-9 CE1104
9-10
10-11 CE1104
CO021
11-12
12-13
13-14
14-15
15-16
16-17
17-18
18-19
19-20
20-21
21-22
Lecture
Exercise, TP
Project, other

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• Autumn semester
• Winter sessions
• Spring semester
• Summer sessions
• Lecture in French
• Lecture in English
• Lecture in German