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Algorithms of the Copula Fit to the Nonlinear Processes in the Utility Industry
Riga Technical University, Latvia.ORCID-id: 0000-0001-9438-3441
Riga Technical University, Latvia.ORCID-id: 0000-0001-8001-7037
Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, Utbildningsvetenskap och Matematik. (MAM)ORCID-id: 0000-0002-0139-0747
2017 (engelsk)Inngår i: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 104, s. 572-577Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Our research studies the construction and estimation of copula-based semi parametric Markov model for the processes, which involved in water flows in the hydro plants. As a rule analyzing the dependence structure of stationary time series regressive models defined by invariant marginal distributions and copula functions that capture the temporal dependence of the processes is considered. This permits to separate out the temporal dependence (such as tail dependence) from the marginal behavior (such as fat tails) of a time series. Dealing with utility company data we have found the best copula describing data - Gumbel copula. As a result constructed algorithm was used for an imitation of low probability events (in a hydro power industry) and predictions.

sted, utgiver, år, opplag, sider
Elsevier, 2017. Vol. 104, s. 572-577
Emneord [en]
Copula; Diffusion processes; Time series; Semi parametric regressions
HSV kategori
Forskningsprogram
matematik/tillämpad matematik
Identifikatorer
URN: urn:nbn:se:mdh:diva-34990DOI: 10.1016/j.procs.2017.01.174ISI: 000399478800076Scopus ID: 2-s2.0-85016014425OAI: oai:DiVA.org:mdh-34990DiVA, id: diva2:1078168
Konferanse
ICTE 2016, December 2016, Riga, Latvia
Tilgjengelig fra: 2017-03-02 Laget: 2017-03-02 Sist oppdatert: 2017-09-28bibliografisk kontrollert

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