Trend-cycle estimation using fuzzy transform of higher degree

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F18%3AA1901H9U" target="_blank" >RIV/61988987:17610/18:A1901H9U - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.22111/ijfs.2017.3067" target="_blank" >http://dx.doi.org/10.22111/ijfs.2017.3067</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.22111/ijfs.2017.3067" target="_blank" >10.22111/ijfs.2017.3067</a>

Result language
angličtina
Original language name
Trend-cycle estimation using fuzzy transform of higher degree
Original language description
In this paper, we provide theoretical justication for the appli-cation of higher degree fuzzy transform in time series analysis. Under theassumption that a time series can be additively decomposed into a trend-cycle, a seasonal component and a random noise, we demonstrate that thehigher degree fuzzy transform technique can be used for the estimation of the trend-cycle, which is one of the basic tasks in time series analysis. We prove that high frequencies appearing in the seasonal component can be arbitrarily suppressed and that random noise, as a stationary process, can be successfully decreased using the fuzzy transform of higher degree with a reasonable adjustment of parameters of a generalized uniform fuzzy partition.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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