Model selection and validation methods for non-linear systems

DOI10.1080/00207178708933730zbMath0617.93069OpenAlexW2011406020MaRDI QIDQ3754542

I. J. Leontaritis, Stephen A. Billings

Publication date: 1987

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207178708933730

zbMATH Keywords

hypothesis testinglikelihood ratiolog determinant ratio

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Nonlinear systems in control theory (93C10) Discrete-time control/observation systems (93C55) Identification in stochastic control theory (93E12)

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Cites Work

• Unnamed Item
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• Dynamic system identification. Experiment design and data analysis
• Maximum likelihood and prediction error methods
• Factorization methods for discrete sequential estimation
• Estimating the dimension of a model
• Fitting autoregressive models for prediction
• On the problem of ambiguities in maximum likelihood identification
• System identification. A survey
• Input-output parametric models for non-linear systems Part I: deterministic non-linear systems
• Selection of the order of an autoregressive model by Akaike's information criterion
• On model structure testing in system identification
• A Bayesian comparison of different classes of dynamic models using empirical data