VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Resampling Methods
Resampling-Methoden
Last Updated: 2026-02-05 15:23:46
Abstract
This course covers several generally useful statistical methods:Nonparametric tests, randomization tests, jackknife and bootstrap, as well as asymptotic approximations and robustness properties of estimators.
Objective
For the classical parametric models there are optimal statistical estimators and test statistics, and their distributions can often be determined exactly. The methods covered in this course allow for finding statisticsl procedures for more general models and to derive exact or approximate distributions of complicated estimators and test statistics. They thus make it possible to use specific models for any applications under consideration and to derive corresponding statistical procedures.
Content
Nonparametric tests, randomization tests, jackknife and bootstrap, asymptotic approximations and robustness properties of estimators.
Resources
Lecture Notes
stat.ethz.ch/~stahel/courses/resampling
Literature
Only for parts of the course author = {A. C. Davison and D. V. Hinkley}, title = {Bootstrap methods and their application}, publisher = {Cambridge University Press}, year = 1997, note = {includes 1 disk}, series = {Cambridge Series in Statistical and Probabilistic Mathematics}
General Information
- Language
- German
- Levels
- MSC
- Frequency
- Every two years
Examination
- Type
- ungraded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise |
Resampling-Methoden
Does not take place this semester.
|
No time listed | 20 h semesterly |