Sequential Estimation of Mixtures in Diffusion Networks

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00431479" target="_blank" >RIV/67985556:_____/15:00431479 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/LSP.2014.2353652" target="_blank" >http://dx.doi.org/10.1109/LSP.2014.2353652</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/LSP.2014.2353652" target="_blank" >10.1109/LSP.2014.2353652</a>

Result language
angličtina
Original language name
Sequential Estimation of Mixtures in Diffusion Networks
Original language description
The letter studies the problem of sequential estimation of mixtures in diffusion networks whose nodes communicate only with their adjacent neighbors. The adopted quasi-Bayesian approach yields a probabilistically consistent and computationally non-intensive and fast method, applicable to a wide class of mixture models with unknown component parameters and weights. Moreover, if conjugate priors are used for inferring the component parameters, the solution attains a closed analytic form.
Czech name
—
Czech description
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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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Project
<a href="/en/project/GP14-06678P" target="_blank" >GP14-06678P: Distributed dynamic estimation in diffusion networks</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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