Asymptotic properties of prediction error estimators in approximate system identification

DOI10.1080/17442508808833507zbMath0648.60048OpenAlexW2019345904MaRDI QIDQ5903687

Andrew J. Heunis

Publication date: 1988

Published in: Stochastics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17442508808833507

zbMATH Keywords

prediction errorcentral limit theoremslaws of iterated logarithmrates of convergence of prediction error estimators

Mathematics Subject Classification ID

Signal detection and filtering (aspects of stochastic processes) (60G35) Identification in stochastic control theory (93E12) Functional limit theorems; invariance principles (60F17)

Related Items (1)

Consistent parameter bounding identification for linearly parametrized model sets

Cites Work

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• Almost sure invariance principles for partial sums of mixing B-valued random variables
• A strong convergence theorem for Banach space valued random variables
• Approximation theorems for independent and weakly dependent random vectors
• Some Useful Functions for Functional Limit Theorems
• Invariance Principles in Statistics, Correspondent Paper
• Prediction error identification methods for stationary stochastic processes
• Convergence analysis of parametric identification methods
• An invariance principle for the law of the iterated logarithm
• Log log law for Gaussian processes

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