Recursive Estimation of Mixtures of Exponential and Normal Distributions
Result description
The paper deals with estimation of a mixture of normal and exponential distributions with the dynamic model of their switching. A separate estimation of normal or exponential mixtures is solved by various approaches in many papers over the world. However, in some application areas, data are of such a nature that they should be described by a combination of exponential and normal models. The paper proposes a recursive Bayesian algorithm of estimation of such a mixture based on continuously measured data.Specific tasks the paper solves are: (i) parameter estimation of both the types of components; (ii) parameter estimation of the dynamic switching model and (iii) detection of the currently active component. Results of experiments with real data are demonstrated.
Keywords
recursive mixture estimationmixture of different distributionsdynamic switching modelexponential distribution
The result's identifiers
Result code in IS VaVaI
Result on the web
DOI - Digital Object Identifier
Alternative languages
Result language
angličtina
Original language name
Recursive Estimation of Mixtures of Exponential and Normal Distributions
Original language description
The paper deals with estimation of a mixture of normal and exponential distributions with the dynamic model of their switching. A separate estimation of normal or exponential mixtures is solved by various approaches in many papers over the world. However, in some application areas, data are of such a nature that they should be described by a combination of exponential and normal models. The paper proposes a recursive Bayesian algorithm of estimation of such a mixture based on continuously measured data.Specific tasks the paper solves are: (i) parameter estimation of both the types of components; (ii) parameter estimation of the dynamic switching model and (iii) detection of the currently active component. Results of experiments with real data are demonstrated.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)
ISBN
978-1-4673-8361-5
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
137-142
Publisher name
IEEE
Place of publication
Piscataway
Event location
Warsaw
Event date
Sep 24, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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Basic information
Result type
D - Article in proceedings
CEP
BB - Applied statistics, operational research
Year of implementation
2015