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rdf:type
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Description
| - We consider the problem of online prediction when it is uncertain what the best prediction model to use is. We develop a method called Dynamic Model Averaging (DMA) in which a state space model for the parameters of each model is combined with a Markov chain model for the correct model. This allows the /correct%22 model to vary over time. The state space and Markov chain models are both specied in terms of forgetting, leading to a highly parsimonious representation. As a special case, when the model and parameters do not change, DMA is a recursive implementation of standard Bayesian model averaging, which we call recursive model averaging (RMA). The method is applied to the problem of predicting the output strip thickness for a cold rolling mill, where the output is measured with a time delay.
- We consider the problem of online prediction when it is uncertain what the best prediction model to use is. We develop a method called Dynamic Model Averaging (DMA) in which a state space model for the parameters of each model is combined with a Markov chain model for the correct model. This allows the /correct%22 model to vary over time. The state space and Markov chain models are both specied in terms of forgetting, leading to a highly parsimonious representation. As a special case, when the model and parameters do not change, DMA is a recursive implementation of standard Bayesian model averaging, which we call recursive model averaging (RMA). The method is applied to the problem of predicting the output strip thickness for a cold rolling mill, where the output is measured with a time delay. (en)
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Title
| - Online Prediction under Model Uncertainty Via Dynamic Model Averaging: Application to a Cold Rolling Mill
- Online Prediction under Model Uncertainty Via Dynamic Model Averaging: Application to a Cold Rolling Mill (en)
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skos:prefLabel
| - Online Prediction under Model Uncertainty Via Dynamic Model Averaging: Application to a Cold Rolling Mill
- Online Prediction under Model Uncertainty Via Dynamic Model Averaging: Application to a Cold Rolling Mill (en)
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skos:notation
| - RIV/67985556:_____/10:00342595!RIV11-MSM-67985556
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
| - P(1M0572), P(7D09008), Z(AV0Z10750506)
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http://linked.open...iv/cisloPeriodika
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/67985556:_____/10:00342595
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - prediction; rolling mills; Bayesian Dynamic Averaging (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...odStatuVydavatele
| - US - Spojené státy americké
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http://linked.open...ontrolniKodProRIV
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http://linked.open...i/riv/nazevZdroje
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...v/svazekPeriodika
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http://linked.open...iv/tvurceVysledku
| - Ettler, P.
- Kárný, Miroslav
- Raftery, A. E.
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http://linked.open...ain/vavai/riv/wos
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http://linked.open...n/vavai/riv/zamer
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issn
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number of pages
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