Experiment design in a bounded-error context: Comparison with D- optimality

DOI10.1016/0005-1098(89)90006-XzbMath0686.62050OpenAlexW2035395596MaRDI QIDQ1262662

Éric Walter, Luc Pronzato

Publication date: 1989

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0005-1098(89)90006-x

zbMATH Keywords

identificationestimationnoise distributionmeasurement errorsmembershipD- optimalitynew optimality criterionnoise boundsnumber of measurements

Mathematics Subject Classification ID

Optimal statistical designs (62K05)

Related Items

Minimum-volume ellipsoids containing compact sets: Application to parameter bounding ⋮ Optimal estimation theory for dynamic systems with set membership uncertainty: An overview ⋮ An inverse method for bounded error parameter identification ⋮ Experiment design in a bounded-error context: Comparison with D- optimality ⋮ On the optimal worst-case experiment design for constrained linear systems

Cites Work

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• Dynamic system identification. Experiment design and data analysis
• Robust experiment design via stochastic approximation
• Identification and application of bounded-parameter models
• Robust experiment design via maximin optimization
• On the value of information in system identification-bounded noise case
• An analytical expression and an algorithm for the volume of a convex polyhedron in \(R^ n\).
• Experiment design in a bounded-error context: Comparison with D- optimality
• DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS
• Optimum Designs in Regression Problems
• Exact recursive polyhedral description of the feasible parameter set for bounded-error models
• Optimal sampling schedule for parameter estimation of linear models with unknown but bounded measurement errors
• Convex design theory¹
• Estimation theory and uncertainty intervals evaluation in presence of unknown but bounded errors: Linear families of models and estimators
• Optimal input signals for parameter estimation in dynamic systems--Survey and new results
• On optimal choice of sampling strategies for linear system identification
• The Design of Experiments for Parameter Estimation
• Locally Optimal Designs for Estimating Parameters