Parameter tracking with partial forgetting method
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F12%3A00370448" target="_blank" >RIV/67985556:_____/12:00370448 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1002/acs.1270" target="_blank" >http://dx.doi.org/10.1002/acs.1270</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/acs.1270" target="_blank" >10.1002/acs.1270</a>
Alternative languages
Result language
angličtina
Original language name
Parameter tracking with partial forgetting method
Original language description
This paper concerns the Bayesian tracking of slowly varying parameters of a linear stochastic regression model. The modelled and predicted system output is assumed to possess time-varying mean value, whereas its dynamics are relatively stable. The proposed estimation method models the system output mean value by time-varying offset. It formulates three extreme hypotheses on model parameters? variability: (i) no parameter varies; (ii) all parameters vary; and (iii) the offset varies. The Bayesian paradigm then provides a mixture as posterior distribution, which is appropriately projected to a feasible class. Exponential forgetting at second? hypotheses level allows tracking of slow variations of respective hypotheses.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA102%2F08%2F0567" target="_blank" >GA102/08/0567: Fully probabilistic design of dynamic decision strategies</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Adaptive Control and Signal Processing
ISSN
1099-1115
e-ISSN
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Volume of the periodical
26
Issue of the periodical within the volume
1
Country of publishing house
GB - UNITED KINGDOM
Number of pages
12
Pages from-to
1-12
UT code for WoS article
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EID of the result in the Scopus database
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