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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Format: | Article |
Language: | English |
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Norwegian Society of Automatic Control
1985-01-01
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Series: | Modeling, Identification and Control |
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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. |
first_indexed | 2024-12-11T05:03:58Z |
format | Article |
id | doaj.art-979e7eac071741f59fa5b4985af358eb |
institution | Directory Open Access Journal |
issn | 0332-7353 1890-1328 |
language | English |
last_indexed | 2024-12-11T05:03:58Z |
publishDate | 1985-01-01 |
publisher | Norwegian Society of Automatic Control |
record_format | Article |
series | Modeling, Identification and Control |
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 |