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Statements

Subject Item
n2:RIV%2F00216275%3A25410%2F14%3A39898345%21RIV15-MSM-25410___
rdf:type
skos:Concept n18:Vysledek
rdfs:seeAlso
http://www.cmsim.eu/papers_pdf/april_2014_papers/8_CMSIM-Journal_2014_Kriz_Knezackova_2_199-206.pdf
dcterms:description
The goal of this paper is to find chaos in the Gross domestic product (GDP) growth rate of selected European countries. We chose only those European countries where data is available since 1980, because we needed the longest time series possible. These are the following states: Belgium, Finland, France, Norway, Spain, Switzerland and United Kingdom. At first we will estimate the time delay and the embedding dimension, which is needed for the largest Lyapunov exponent estimation. The largest Lyapunov exponent is one of the important indicators of chaos and is generally wellknown. Subsequently we will calculate the 0-1 test for chaos. Finally we will compute the Hurst exponent by using the Rescaled Range analysis. The Hurst exponent is a numerical estimate of the predictability of a time series. The results indicated that chaotic behaviors obviously exist in GDP growth rate. The goal of this paper is to find chaos in the Gross domestic product (GDP) growth rate of selected European countries. We chose only those European countries where data is available since 1980, because we needed the longest time series possible. These are the following states: Belgium, Finland, France, Norway, Spain, Switzerland and United Kingdom. At first we will estimate the time delay and the embedding dimension, which is needed for the largest Lyapunov exponent estimation. The largest Lyapunov exponent is one of the important indicators of chaos and is generally wellknown. Subsequently we will calculate the 0-1 test for chaos. Finally we will compute the Hurst exponent by using the Rescaled Range analysis. The Hurst exponent is a numerical estimate of the predictability of a time series. The results indicated that chaotic behaviors obviously exist in GDP growth rate.
dcterms:title
The Presence of Chaos in the GDP Growth Rate Time Series The Presence of Chaos in the GDP Growth Rate Time Series
skos:prefLabel
The Presence of Chaos in the GDP Growth Rate Time Series The Presence of Chaos in the GDP Growth Rate Time Series
skos:notation
RIV/00216275:25410/14:39898345!RIV15-MSM-25410___
n4:aktivita
n16:S
n4:aktivity
S
n4:cisloPeriodika
2
n4:dodaniDat
n8:2015
n4:domaciTvurceVysledku
n6:1687999 n6:9151613
n4:druhVysledku
n15:J
n4:duvernostUdaju
n9:S
n4:entitaPredkladatele
n14:predkladatel
n4:idSjednocenehoVysledku
39091
n4:idVysledku
RIV/00216275:25410/14:39898345
n4:jazykVysledku
n12:eng
n4:klicovaSlova
largest Lyapunov exponent; Hurst exponent; Phase Space Reconstruction; Time series analysis; GDP growth rate; GDP; Chaos theory
n4:klicoveSlovo
n5:Hurst%20exponent n5:largest%20Lyapunov%20exponent n5:GDP n5:Phase%20Space%20Reconstruction n5:Chaos%20theory n5:GDP%20growth%20rate n5:Time%20series%20analysis
n4:kodStatuVydavatele
GR - Řecká republika
n4:kontrolniKodProRIV
[F1FFC95D6D55]
n4:nazevZdroje
Chaotic Modeling and Simulation (CMSIM)
n4:obor
n10:AH
n4:pocetDomacichTvurcuVysledku
2
n4:pocetTvurcuVysledku
2
n4:rokUplatneniVysledku
n8:2014
n4:svazekPeriodika
2014
n4:tvurceVysledku
Knězáčková, Radka Kříž, Radko
s:issn
2241-0503
s:numberOfPages
8
n17:organizacniJednotka
25410