Dynamic structural systems under indirect observation: Identifiability and estimation aspects from a system theoretic perspective

DOI10.1007/BF02294064zbMath0621.62107WikidataQ115059072 ScholiaQ115059072MaRDI QIDQ1090052

Pieter W. Otter

Publication date: 1986

Published in: Psychometrika (Search for Journal in Brave)

zbMATH Keywords

observabilitycontrollabilitymaximum likelihoodKalman-Bucy filtersnon-linear estimationindirect observationJöreskog's LISREL procedurelatent vectors estimationlinear stochastic state space modelslocal parameter identifiabilitystructural dynamic models with latent variables

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Factor analysis and principal components; correspondence analysis (62H25) Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12)

Related Items (6)

Analytical uses of Kalman filtering in econometrics — A survey ⋮ Modeling data revisions: measurement error and dynamics of ``true values ⋮ Fitting longitudinal reduced-rank regression models by alternating least squares ⋮ Dynamic factor analysis of nonstationary multivariate time series ⋮ Decomposition of neurological multivariate time series by state space modelling ⋮ BLIND SIGNAL SEPARATION OF MIXTURES OF CHAOTIC PROCESSES: A COMPARISON BETWEEN INDEPENDENT COMPONENT ANALYSIS AND STATE SPACE MODELING

Cites Work

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• Dynamic programming and stochastic control
• Dynamic feature space modelling, filtering and self-tuning control of stochastic systems. A systems approach with economic and social applications
• Dynamic system identification. Experiment design and data analysis

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