About: ARMA Models Versus an SVM Model Applied to Wages Time Series Modelling and Forecasting.     Goto   Sponge   NotDistinct   Permalink

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Description
  • We investigate the quantifying of statistical and econometric structural model parameters of average nominal wages in Slovak economy. SVM´s modeling approaches are used for automated specification of a functional form of the model. We provide the fit of average nominal wages models based on Box-Jenkins methodology to the quarterly data over the period 1991-2006 in the Slovak Republic. We use this model as a tool to compare its approximation and forecasting abilities with those obtained using SVM´s method.
  • We investigate the quantifying of statistical and econometric structural model parameters of average nominal wages in Slovak economy. SVM´s modeling approaches are used for automated specification of a functional form of the model. We provide the fit of average nominal wages models based on Box-Jenkins methodology to the quarterly data over the period 1991-2006 in the Slovak Republic. We use this model as a tool to compare its approximation and forecasting abilities with those obtained using SVM´s method. (en)
Title
  • ARMA Models Versus an SVM Model Applied to Wages Time Series Modelling and Forecasting.
  • ARMA Models Versus an SVM Model Applied to Wages Time Series Modelling and Forecasting. (en)
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  • ARMA Models Versus an SVM Model Applied to Wages Time Series Modelling and Forecasting.
  • ARMA Models Versus an SVM Model Applied to Wages Time Series Modelling and Forecasting. (en)
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  • RIV/47813059:19240/10:#0003229!RIV11-GA0-19240___
http://linked.open...avai/riv/aktivita
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  • P(GA402/08/0022)
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  • 247736
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  • RIV/47813059:19240/10:#0003229
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  • SVM method; Box-Jenkins methodology; time series forecasring (en)
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  • [CAB83E197A96]
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  • INFOKOM-4 Infokommunikacionnye technologii v nauke, proizvodstve i obrazovanii
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  • Marček, Dušan
  • Horváth, M.
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issn
  • 2219-293X
number of pages
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  • Izdateľstvo Severo-Kavkazskovo gosudarstvennovo techničeskovo universiteta
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  • 19240
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