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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 |
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Requirements
One seminar presentation and final exam.
Completion parts must belong to the same implementation
Principles and baselines related to teaching and learning
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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:
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 |
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Additional information
Suitable for postgraduate studies
Will not be lectured year 2010-2011
More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |
| Practical works |
Contact teaching: 0 % Distance learning: 0 % Self-directed learning: 0 % |