Abstract
The influence functional, developed by Martin and Yohai, is an asymptotic robustness measure of a parameter estimate's sensitivity to the infinitesimal occurrence of correlated outlier contamination of a measurement sequence. Here, the usefulness of the influence functional as a tool for characterizing estimator robustness in system parameter identification is explored. In particular, this utility is illustrated by examining the influence functional as a measure of robustness for the choice of the error‐shaping function in the correlation or instrumental variables approach to system parameter identification.
Original language | English (US) |
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Pages (from-to) | 223-237 |
Number of pages | 15 |
Journal | International Journal of Robust and Nonlinear Control |
Volume | 2 |
Issue number | 3 |
DOIs | |
State | Published - Oct 1992 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Chemical Engineering(all)
- Biomedical Engineering
- Aerospace Engineering
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering
Keywords
- Influence functions
- Outliers
- Robustness
- System identification