Opinto-opas 2005-2006

SGN-2756 ROBUST ESTIMATION, 3 cr
ROBUST ESTIMATION

Person responsible
Assistant Professor Sari Peltonen

Lecturers
Sari Peltonen, Assistant Professor, room TE312, sari.peltonen@tut.fi

Implementation rounds
Implementation 1
  Period 1 Period 2 Period 3 Period 4 Period 5 Summer Language of instruction
Seminar - - - 2 h/week+ 2 h/week - In English only
(Academic Calender 2005-2006)

Objectives
After passing this course the student understands what robustness means and knows which tools can be used for studying robustness of estimators (filters). Student will also be familiar with several robust estimators.

Contents
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.  Spefific properties of these different estimator classes. Redescending M-estimators and matched median filter.    

Requirements for completing the course
One seminar presentation and final exam.

Assessment criteria
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.

  • Used assessment scale is passed / failed

    • Study material
    Type Name Author ISBN URL, edition, availablitity... Exam material Language
    Book "Robust Statistics" Hampel, Ronchetti, Rousseeuw & Stahel   John Wiley, 1985 Yes  English 
    Book "Robust Statistics" Huber   John Wiley, 1981 No  English 
    Lecture slides "Robust Estimation" Sari Peltonen   http://www.cs.tut.fi/~sari/sgn-2756/ Yes  English 

    Prerequisites
    Number Name Credits M/R
    SGN-2706 Nonlinear Signal Processing 5 Recommendable

    Other comments
    From the book by Hampel et al. the first two chapters are studied on this course.

  • Partial passing of course must be in connection with the same round of implementation.
  • The course is suitable for postgraduate studies.
  • Course will not be lectured in the academic year 2005-2006.

    • Correspondence of content
    8001552 Robust Estimation

    Course homepage

    Last modified 22.02.2005
    Modified byAntti Niemistö