Autoregressive Model with Partial Forgetting within Rao-Blackwellized Particle Filter
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F12%3A00370444" target="_blank" >RIV/67985556:_____/12:00370444 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21260/12:00187538
Result on the web
<a href="http://dx.doi.org/10.1080/03610918.2011.598992" target="_blank" >http://dx.doi.org/10.1080/03610918.2011.598992</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/03610918.2011.598992" target="_blank" >10.1080/03610918.2011.598992</a>
Alternative languages
Result language
angličtina
Original language name
Autoregressive Model with Partial Forgetting within Rao-Blackwellized Particle Filter
Original language description
The authors are concerned with Bayesian identification and prediction of a nonlinear discrete stochastic process. The fact that a nonlinear process can be approximated by a piecewise linear function advocates the use of adaptive linear models. They propose a linear regression model within Rao-Blackwellized particle filter. The parameters of the linear model are adaptively estimated using a finite mixture, where the weights of components are tuned with a particle filter. The mixture reflects a priori given hypotheses on different scenarios of (expected) parameters' evolution.
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
Result was created during the realization of more than one project. More information in the Projects tab.
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
Communications in Statistics - Simulation and Computation and Communications in Statistics Part B - Simulation and Computation
ISSN
0361-0918
e-ISSN
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Volume of the periodical
41
Issue of the periodical within the volume
5
Country of publishing house
GB - UNITED KINGDOM
Number of pages
8
Pages from-to
582-589
UT code for WoS article
000301342800002
EID of the result in the Scopus database
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