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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2018/2019

Robust Statistics for Cybernetics

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Code Completion Credits Range Language
XP33RSK ZK 4 2+0s Czech
Lecturer:
Jana Nosková (guarantor)
Tutor:
Jana Nosková (guarantor)
Supervisor:
Department of Cybernetics
Synopsis:

Statistical methods are basic tools of control and decision making theory. Classical statistical methods (e.g. MLE) are usually very sensitive to deviations from our idealized model. Thus many methods which are robust have been developed. It means that these methods are not so sensitive to small deviations from an underlying model. So we briefly explain the parametric concept of estimation and then we introduce the robust approach, some basic robust estimators of location (e.g. trimmed mean, Hampel estimator) and measures of robustness (influence function, breakdown point).

Requirements:
Syllabus of lectures:
Syllabus of tutorials:
Study Objective:
Study materials:

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 2018/2019:
Time-table is not available yet
Time-table for summer semester 2018/2019:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2019-03-22
For updated information see http://bilakniha.cvut.cz/en/predmet11604104.html