Course Catalog 2010-2011
Postgraduate

Basic Pori International Postgraduate Open University

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Course Catalog 2010-2011

SGN-2756 Robust Estimation, 3 cr

Person responsible

Sari Peltonen

Lessons

Study type P1 P2 P3 P4 Summer Implementations Lecture times and places
            SGN-2756 2011-03  

Requirements

One seminar presentation and final exam.
Completion parts must belong to the same implementation

Principles and baselines related to teaching and learning

-

Learning outcomes

After completing the course, the student - is able to explain the meaning of robustness, deviations from parametric models and estimation theory, - can apply tools (influence function (IF), gross-error sensitivity, local-shift sensitivity, rejection point, asymptotic variance, breakdown point) for assessing the robustness of estimators, - is able to design basic robust estimators, and - is able to prepare and present a presentation on a robustness related topic.

Content

Content Core content Complementary knowledge Specialist knowledge
1. The meaning of robustness, deviations from parametric models and estimation theory.  Chebychev's inequality, information inequality, unbiasedness, consistency, efficiency and basics of detection.  Minimax approach. 
2. Influence function (IF), gross-error sensitivity, local-shift sensitivity, rejection point, asymptotic variance, breakdown point.  Finite-sample versions of the IF and output distributional influence function (ODIF).   
3. Order Statistics (OS) and stack filters and their distributions.  Optimization of the stack filters.   
4. Definitions of M-, L-, and R-estimators.  Specific properties of these different estimator classes. Redescending M-estimators and matched median filter.   

Evaluation criteria for the course

Grading is pass/fail. In order to pass the student has to give seminar presentation and get at least half of the maximum points from the final exam.

Assessment scale:

Evaluation scale passed/failed will be used on the course

Partial passing:

Completion parts must belong to the same implementation

Study material

Type Name Author ISBN URL Edition, availability, ... Examination material Language
Book   Robust Statistics   Hampel, Ronchetti, Rousseeuw & Stahel       John Wiley, 1985      English  
Book   Robust Statistics   Huber       John Wiley, 1981      English  
Book   Robust Statistics   Maronna Ricardo, Martin Doug and Yohai Victor   978-0-470-01092-1     John Wiley, 2006      English  
Lecture slides   Robust Estimation   Sari Peltonen            English  

Prerequisites

Course Mandatory/Advisable Description
SGN-2706 Nonlinear Signal Processing Advisable    

Prerequisite relations (Requires logging in to POP)



Correspondence of content

Course Corresponds course  Description 
SGN-2756 Robust Estimation, 3 cr 8001552 Robust Estimation, 2 cu  

Additional information

Suitable for postgraduate studies
Will not be lectured year 2010-2011

More precise information per implementation

Implementation Description Methods of instruction Implementation
SGN-2756 2011-03   Practical works
   
Contact teaching: 0 %
Distance learning: 0 %
Self-directed learning: 0 %  

Last modified26.01.2011