Algorithms for global total least squares modelling of finite multivariable time series

DOI10.1016/0005-1098(94)00114-XzbMath0824.93063OpenAlexW2045131550MaRDI QIDQ1892997

Berend Roorda

Publication date: 9 November 1995

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0005-1098(94)00114-x

zbMATH Keywords

identificationlinear systemsmodellingtime seriesKalman filtersstate spaceGauss-Newton methodtime-invariantglobal total least squares

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Multivariable systems, multidimensional control systems (93C35) Linear systems in control theory (93C05) Identification in stochastic control theory (93E12)

Related Items (10)

Rational representation of behaviors: Interconnectability and stabilizability ⋮ Maximum likelihood identification of noisy input-output models ⋮ Deterministic Kalman filtering in a behavioral framework ⋮ Identification of factor models by behavioural and subspace methods ⋮ Weighted norms in subspace-based methods for time series analysis ⋮ Local stability in the problem of identifying coefficients of a linear difference equation ⋮ Structured low-rank approximation and its applications ⋮ Misfit versus latency ⋮ Optimal angle reduction -- a behavioral approach to linear system approximation ⋮ Optimal errors-in-variables filtering

Cites Work

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• From time series to linear system. I: Finite dimensional linear time invariant systems
• From time series to linear system, II. Exact modelling
• From time series to linear system, III: Approximate modelling
• Global total least squares modeling of multivariable time series

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