Number of hours
- Lectures 16.5
- Projects -
- Tutorials 16.5
- Internship -
- Laboratory works -
- Written tests -
ECTS
ECTS 3.0
Goal(s)
This course presents the mathematical theory of statistical inference. It deepens and completes the Statistical Principles and Methods course.
Responsible(s)
Olivier GAUDOIN
Content(s)
1. Concepts of statistical inference. Statistical model. Likelihood. Sufficiency.
2. Optimal parametric estimation. Minimum variance unbiased estimation. Fisher Information.
3. Maximum likelihood estimation. Likelihood ratio tests.
4. Nonparametric estimation. Order and rank statistics.
5. Extreme values statistics.
6. Functional estimation.
Probability Theory and Applications, Statistical Principles and Methods (first year).
Test
Evaluation : Examen Ecrit (3h)
Resit : Examen Ecrit (2h)
Session 1: written exam (3 hours, handwritten documents allowed) (E).
Session 2: written exam (2 hours, handwritten documents allowed) (E).
Calendar
The course exists in the following branches:
- Curriculum - Financial Engineering - Semester 8
- Curriculum - Math. Modelling, Image & Simulation - Semester 8
Additional Information
Course ID : 4MMSIA6
Course language(s): 
The course is attached to the following structures:
- Team Probability-Statistics
You can find this course among all other courses.
Bibliography
Polycopié de cours.
D. FOURDRINIER : Statistique inférentielle, Dunod, 2002.
J.A. RICE : Mathematical Statistics and Data Analysis, Duxbury Press, 2006.
G. SAPORTA : Probabilités, analyse des données et statistique, Technip, 2011.
J. SHAO : Mathematical Statistics, Springer, 2003.
P. TASSI : Méthodes statistiques, Economica, 2004.