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Topics in nonparametric smoothing

academic year
The health crisis linked to the spread of Covid-19 constitutes grounds of force majeure constraining the University to adapt the assessment methods for some of the course units; Information on the new terms of these assessments will be provided to students through the usual information channels by December 4, 2020.

Course teacher(s)

Maarten JANSEN (Coordinator)

ECTS credits


Language(s) of instruction


Course content

Study of at least one of the following topics: (1) spline smoothing (2) kernel or multiscale local polynomial estimation (3) wavelet or multiscale smoothing.

Objectives (and/or specific learning outcomes)

The course is about nonparametric regression or density estimation (nonparametric should not be understood as distribution free here, but rather refers to a nonspecified or observation dependent model for the covariate-response relationship)

Teaching methods and learning activities

Literature study with focus on one or several aspects (theoretic, computational, application) and one or several smoothing techniques

Reproduction of research results (proofs and/or simulation studies)

Contribution to the teaching profile

Nonparametric statistics

Other information


Maarten Jansen, see http://homepages.ulb.ac.be/%7Emajansen/index.html for contact information


Method(s) of evaluation

  • Other

Written report and regular meetings/intermediate discussions of progress