Fiches de cours

Robust and nonparametric statistics

MATH-441

Enseignant(s) :

Morgenthaler Stephan

Langue:

English

Remarque

Cours donné en alternance sur deux ans (donné en 2019-20)

Summary

In the decades from 1930 to 1950, many rank-based statistics were introduced. These methods were received with much interest, because they worked under weak conditions. Starting in the late 1950, a theory of robustness was added. The course gives an overview of these two approaches to data analysis.

Content

I. Robust Statistics

II. Linear Rank Tests

III. Estimation of smooth functions

Learning Prerequisites

Required courses

Introduction to Probability, Introduction to Statistics

Learning Outcomes

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

Transversal skills

Teaching methods

Ex cathedra lecture and exercises in the classroom

Expected student activities

Do all the exercices. Prepare each week for the course. Participate actively in the course.

Assessment methods

Oral exam.

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

Introduction to the theory of nonparametric statistics by R.H. Randles and D.A. Wolfe, Wiley.

All of nonparametric statistics by L. Wasserman, Springer.

Robust Statistics: The approach based on influence functions by F.R. Hampel, E.M. Ronchetti, P.J. Rousseeuw, W.A. Stahel, Wiley.

Robust Statistics by P.J. Huber, Wiley (second edition).

Robust Statistics: Theory and Methods by D.R. Martin, M. Salibian-Barrera, R.A. Maronna, V.J. Yohai, Wiley.

Ressources en bibliothèque

Dans les plans d'études

  • Mathématiques - master, 2019-2020, Master semestre 2
    • Semestre
      Printemps
    • Forme de l'examen
      Oral
    • Crédits
      5
    • Matière examinée
      Robust and nonparametric statistics
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Data Science, 2019-2020, Master semestre 2
    • Semestre
      Printemps
    • Forme de l'examen
      Oral
    • Crédits
      5
    • Matière examinée
      Robust and nonparametric statistics
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Data Science, 2019-2020, Master semestre 4
    • Semestre
      Printemps
    • Forme de l'examen
      Oral
    • Crédits
      5
    • Matière examinée
      Robust and nonparametric statistics
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Ingénierie mathématique, 2019-2020, Master semestre 2
    • Semestre
      Printemps
    • Forme de l'examen
      Oral
    • Crédits
      5
    • Matière examinée
      Robust and nonparametric statistics
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Ingénierie mathématique, 2019-2020, Master semestre 4
    • Semestre
      Printemps
    • Forme de l'examen
      Oral
    • Crédits
      5
    • Matière examinée
      Robust and nonparametric statistics
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines

Semaine de référence

LuMaMeJeVe
8-9
9-10
10-11
11-12
12-13
13-14
14-15
15-16
16-17
17-18
18-19
19-20
20-21
21-22
En construction
Cours
Exercice, TP
Projet, autre

légende

  • Semestre d'automne
  • Session d'hiver
  • Semestre de printemps
  • Session d'été
  • Cours en français
  • Cours en anglais
  • Cours en allemand