Coursebooks 2017-2018

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Mathematical modelling of behavior

MATH-463

Lecturer(s) :

Bierlaire Michel

Language:

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

1. Introduction and examples
2. Choice theory
3. Data
4. Binary choice
5. Multinomial choice
6. Nested Logit model
7. Multivariate extreme Value models
8. Tests
9. Prediction
10. Sampling
11. Large scale problems
12. Mixed models.

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

Flipped classroom: the students will be provided with various material to be introduced to the concepts. The ex cathedra lectures will provide deeper descriptions, and invole discussions and clarifications. 

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.

Ressources en bibliothèque

In the programs

Reference week

 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