Robust statistics

Garant předmětu:

Jana Nosková

Lecturer:

Jana Nosková

Tutor:

Supervisor:

Department of Mathematics

Synopsis:

Robust statistics deals with statistical methods which are not sensitive to small depatrures from model assumptions. Robust statistics became a part of mainstream statistics only a few years ago yet it is implemented in many statistical softwars.

Requirements:

Syllabus of lectures:

Syllabus of tutorials:

Study Objective:

Study materials:

Ricardo A. Maronna, R. Douglas Martin, Victor J. Yohai, Matías Salibián-Barrera, Robust Statistics: Theory and Methods (with R), 2nd Edition

ISBN: 978-1-119-21466-3 October 2018 464 Pages

Jureckova,J. (2001) Robustni statisticke metody, Karolinum Praha

Rousseeuw,P.J., Leroy,A. (1987) Robust Regression and Outlier Detection. Wiley, New York

Huber,P.J. (1981) Robust Statistics.Wiley,New York

Hampel,F.R.,Ronchetti, E.M.,Rousseeuw, P.J.,Stahel,W.A. (1986) Robust Statistics: The Approach Based on Influence Functions. Wiley,New York

Dodge,Y., Jureckova,J. (2000) Adaptive Regression. Springer, New York

Note:

Time-table for winter semester 2023/2024:

Time-table is not available yet

Time-table for summer semester 2023/2024:

Time-table is not available yet

The course is a part of the following study plans: