Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

401-6201-00L  Resampling Methods

SemesterAutumn Semester 2015
LecturersL. Meier
Periodicitytwo-yearly recurring course
Language of instructionEnglish
CommentSpecial Students "University of Zurich (UZH)" in the Master Program in Biostatistics at UZH cannot register for this course unit electronically. Forward the lecturer's written permission to attend to the Registrar's Office. Alternatively, the lecturer may also send an email directly to kanzlei@rektorat.ethz.ch. The Registrar's Office will then register you for the course.


AbstractThis course covers several generally useful statistical methods:
Nonparametric tests, randomization tests, jackknife and bootstrap, as well as asymptotic approximations and robustness properties of estimators.
ObjectiveFor 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.
ContentNonparametric tests, randomization tests, jackknife and bootstrap, asymptotic approximations and robustness properties of estimators.
Lecture noteshttp://stat.ethz.ch/~meier/teaching/resampling/
LiteratureOnly 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}
Prerequisites / NoticeThis course is part of the programme for the certificate and diploma in Advanced Studies in Applied Statistics. It is given every second year in the winter semester break.