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Statements

Subject Item
n2:RIV%2F00216275%3A25410%2F13%3A39896597%21RIV14-MSM-25410___
rdf:type
skos:Concept n18:Vysledek
rdfs:seeAlso
http://link.springer.com/chapter/10.1007%2F978-3-319-00542-3_36
dcterms:description
The goal of this paper is to analyze the Czech Gross domestic product (GDP) and to find chaos in the Czech GDP. At first we will estimate the time delay and the embedding dimension, which is needed for the Lyapunov exponent estimation and for the phase space reconstruction. Subsequently we will compute the largest Lyapunov exponent, which is one of the important indicators of chaos. Then we will calculate the 0-1 test for chaos. Finally we will compute the Hurst exponent by Rescaled Range analysis and by dispersional analysis. The Hurst exponent is a numerical estimate of the predictability of a time series. In the end we will display a phase portrait of detrended GDP time series. The results indicated that chaotic behaviors obviously exist in GDP. The goal of this paper is to analyze the Czech Gross domestic product (GDP) and to find chaos in the Czech GDP. At first we will estimate the time delay and the embedding dimension, which is needed for the Lyapunov exponent estimation and for the phase space reconstruction. Subsequently we will compute the largest Lyapunov exponent, which is one of the important indicators of chaos. Then we will calculate the 0-1 test for chaos. Finally we will compute the Hurst exponent by Rescaled Range analysis and by dispersional analysis. The Hurst exponent is a numerical estimate of the predictability of a time series. In the end we will display a phase portrait of detrended GDP time series. The results indicated that chaotic behaviors obviously exist in GDP.
dcterms:title
Chaotic Analysis of the GDP Time Series Chaotic Analysis of the GDP Time Series
skos:prefLabel
Chaotic Analysis of the GDP Time Series Chaotic Analysis of the GDP Time Series
skos:notation
RIV/00216275:25410/13:39896597!RIV14-MSM-25410___
n18:predkladatel
n19:orjk%3A25410
n3:aktivita
n5:I
n3:aktivity
I
n3:cisloPeriodika
2013
n3:dodaniDat
n10:2014
n3:domaciTvurceVysledku
n4:1687999
n3:druhVysledku
n20:J
n3:duvernostUdaju
n17:S
n3:entitaPredkladatele
n7:predkladatel
n3:idSjednocenehoVysledku
64997
n3:idVysledku
RIV/00216275:25410/13:39896597
n3:jazykVysledku
n13:eng
n3:klicovaSlova
time series analysis; Phase Space Reconstruction; largest Lyapunov exponent; Hurst exponent; GDP; chaos theory
n3:klicoveSlovo
n9:Hurst%20exponent n9:Phase%20Space%20Reconstruction n9:time%20series%20analysis n9:chaos%20theory n9:GDP n9:largest%20Lyapunov%20exponent
n3:kodStatuVydavatele
NL - Nizozemsko
n3:kontrolniKodProRIV
[21BB6A286A3D]
n3:nazevZdroje
Advances in Intelligent Systems and Computing
n3:obor
n16:AH
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:rokUplatneniVysledku
n10:2013
n3:svazekPeriodika
210
n3:tvurceVysledku
Kříž, Radko
s:issn
2194-5357
s:numberOfPages
10
n14:doi
10.1007/978-3-319-00542-3_36
n15:organizacniJednotka
25410