Duration
30h Th, 10h Pr, 20h Mon. WS
Number of credits
| Master in mathematics, research focus (Even years, organized in 2024-2025) | 8 crédits | |||
| Master in mathematics, teaching focus (Even years, organized in 2024-2025) | 8 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
This course develops the following themes:
- Ranks and quantiles;
- Non parametric univariate tests;
- Non parametric estimation of density functions;
- Non parametric and quantile regression;
Learning outcomes of the learning unit
At the end of the course, students will be able to use, in an appropriate way, nonparametric techniques in inference, regression and density estimation. They will be prepared to set up and interpret regression models in finte or infite dimensional setting.
Prerequisite knowledge and skills
Inferential statistics and probabilty theory.
The course combine a practical approach with the development of theory. It is especially designed for mathematicians.
Planned learning activities and teaching methods
The course will be divided in ex-cathedra lectures for the theory and discussion sessions about the results of the practicals obtanied at home by the students. For the practical, the use of the software R is compulsory (and intensive).
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Course materials and recommended or required readings
Platform(s) used for course materials:
- eCampus
Further information:
Some partial lecture notes are available. Moreover, the slides used during the class will be available on eCampus.
Some refereces:
- D. Bosq (1996). Nonparametric statistics for stochastic processes. Springer-Verlag.
- E.L. Lehmann (1999). Elements of large sample theory. Springer Texts in Statistics. Springer-Verlag.
- A. B. Tsybakov (2004). Introduction à l'estimation non-paramétrique. Springer-Verlag, Berlin, 2004.
- L. Wasserman (2006). All of nonparametric statistics. Springer Texts in Statistics. Springer-Verlag.
Exam(s) in session
Any session
- In-person
written exam ( open-ended questions ) AND oral exam
Further information:
Written exam organised during the exam period for exercises (either by hand or with the software)
Oral exam for theory
Work placement(s)
Organisational remarks and main changes to the course
The course is taught only every other year, on "even" years. It is therefore scheduled in 2024-2025 but not in 2025-2026.
Contacts
Gentiane Haesbroeck