Bayesian Mixture Estimation without Tears

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F21%3A00544577" target="_blank" >RIV/67985556:_____/21:00544577 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21260/21:00350675
Result on the web
<a href="http://dx.doi.org/10.5220/0010508706410648" target="_blank" >http://dx.doi.org/10.5220/0010508706410648</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0010508706410648" target="_blank" >10.5220/0010508706410648</a>

Result language
angličtina
Original language name
Bayesian Mixture Estimation without Tears
Original language description
This paper aims at presenting the on-line non-iterative form of Bayesian mixture estimation. The model used is composed of a set of sub-models (components) and an estimated pointer variable that currently indicates the active component. The estimation is built on an approximated Bayes rule using weighted measured data. The weights are derived from the so called proximity of measured data entries to individual components. The basis for the generation of the weights are integrated likelihood functions with the inserted point estimates of the component parameters. One of the main advantages of the presented data analysis method is a possibility of a simple incorporation of the available prior knowledge. Simple examples with a programming code as well as results of experiments with real data are demonstrated. The main goal of this paper is to provide clear description of the Bayesian estimation method based on the approximated likelihood functions, called proximities.
Czech name
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Czech description
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Project
<a href="/en/project/8A19009" target="_blank" >8A19009: Arrowhead Tools for Engineering of Digitalisation Solutions</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics
ISBN
978-989-758-522-7
ISSN
2184-2809
e-ISSN
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Number of pages
8
Pages from-to
641-648
Publisher name
Scitepress
Place of publication
Setúbal
Event location
Setúbal (online)
Event date
Jul 6, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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