Model selection based on robustness criterion with measurement application

Sofiane Brahim-Belhouari; Gilles Fleury; Marie-Eve Davoust

doi:10.1117/12.351314

25 June 1999 Model selection based on robustness criterion with measurement application

Sofiane Brahim-Belhouari, Gilles Fleury, Marie-Eve Davoust

Proceedings Volume 3816, Mathematical Modeling, Bayesian Estimation, and Inverse Problems; (1999) https://doi.org/10.1117/12.351314
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

Huber's approach to robust estimation is highly fruitful for solving estimation problems with contaminated data or under incomplete information according to the error structure. A simple selection procedure based on robustness to variations of the errors distribution from the assumed one, is proposed. Minimax M-estimator is used to estimate efficiently the parameters and the measurement quantity. A performance deviation criterion is computed by the mean of the Monte Carlo method improved by the Latin Hypercube Sampling. The selection produced is applied to a real measurement problem, grooves dimensioning using Remote Field Eddy Current inspection.

Citation Download Citation

Sofiane Brahim-Belhouari, Gilles Fleury, and Marie-Eve Davoust "Model selection based on robustness criterion with measurement application", Proc. SPIE 3816, Mathematical Modeling, Bayesian Estimation, and Inverse Problems, (25 June 1999); https://doi.org/10.1117/12.351314

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