Estimation of Large-Scale Implicit Models Using 2-Stage Methods

The problem of estimating large scale implicit (non-recursive) models by two- stage methods is considered. The first stage of the methods is used to construct or estimate an explicit form of the total model, by constructing a minimal stochastic realization of the system. This model is then subsequen...

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Main Author: Rolf Henriksen
Format: Article
Language:English
Published: Norwegian Society of Automatic Control 1985-01-01
Series:Modeling, Identification and Control
Subjects:
Online Access:http://www.mic-journal.no/PDF/1985/MIC-1985-1-1.pdf
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author Rolf Henriksen
author_facet Rolf Henriksen
author_sort Rolf Henriksen
collection DOAJ
description The problem of estimating large scale implicit (non-recursive) models by two- stage methods is considered. The first stage of the methods is used to construct or estimate an explicit form of the total model, by constructing a minimal stochastic realization of the system. This model is then subsequently used in the second stage to generate instrumental variables for the purpose of estimating each sub-model separately. This latter stage can be carried out by utilizing a generalized least squares method, but most emphasis is put on utilizing decentralized filtering algorithms and a prediction error formulation. A note about the connection between the original TSLS-method (two-stage least squares method) and stochastic realization is also made.
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spelling doaj.art-979e7eac071741f59fa5b4985af358eb2022-12-22T01:20:05ZengNorwegian Society of Automatic ControlModeling, Identification and Control0332-73531890-13281985-01-016131910.4173/mic.1985.1.1Estimation of Large-Scale Implicit Models Using 2-Stage MethodsRolf HenriksenThe problem of estimating large scale implicit (non-recursive) models by two- stage methods is considered. The first stage of the methods is used to construct or estimate an explicit form of the total model, by constructing a minimal stochastic realization of the system. This model is then subsequently used in the second stage to generate instrumental variables for the purpose of estimating each sub-model separately. This latter stage can be carried out by utilizing a generalized least squares method, but most emphasis is put on utilizing decentralized filtering algorithms and a prediction error formulation. A note about the connection between the original TSLS-method (two-stage least squares method) and stochastic realization is also made.http://www.mic-journal.no/PDF/1985/MIC-1985-1-1.pdfParameter estimationlarge scale systemstwo-stage methodsdecentralized filteringprediction error methods
spellingShingle Rolf Henriksen
Estimation of Large-Scale Implicit Models Using 2-Stage Methods
Modeling, Identification and Control
Parameter estimation
large scale systems
two-stage methods
decentralized filtering
prediction error methods
title Estimation of Large-Scale Implicit Models Using 2-Stage Methods
title_full Estimation of Large-Scale Implicit Models Using 2-Stage Methods
title_fullStr Estimation of Large-Scale Implicit Models Using 2-Stage Methods
title_full_unstemmed Estimation of Large-Scale Implicit Models Using 2-Stage Methods
title_short Estimation of Large-Scale Implicit Models Using 2-Stage Methods
title_sort estimation of large scale implicit models using 2 stage methods
topic Parameter estimation
large scale systems
two-stage methods
decentralized filtering
prediction error methods
url http://www.mic-journal.no/PDF/1985/MIC-1985-1-1.pdf
work_keys_str_mv AT rolfhenriksen estimationoflargescaleimplicitmodelsusing2stagemethods