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Prognose uni- und multivariater Zeitreihen


  • Manfred Deistler
  • Klaus Neusser


Der Aufsatz bietet eine Zusammenfassung der theoretischen Grundlagen der linearen Kleinst-Quadrate-Prognose im Kontext von stationären Prozessen, insbesondere im Zusammenhang von ARMA bzw. ARMAX Systemen. In einem ersten Schritt wird das Prognoseproblem unter der Voraussetzung, dass die zweiten Momente bekannt sind, behandelt. Da diese jedoch meist nicht bekannt sind, geht das Prognoseproblem mit einem Identifikationsproblem einher. Dieses Problem wird eingehend anhand von multivariaten AR-, ARMA- und ARMAX-System erläutert. Da bei der praktischen Anwendung noch andere Gesichtspunkte (a priori Information, Fristigkeit, Aufwand, Geschwindigkeit, etc.) eine Rolle spielen und die Methoden daher eventuell adaptiert werden müssen, werden einige bei der praktischen Anwendung auftretende Probleme anhand der Prognose makroökonomischer und betriebswirtschaftlicher Zeitreihen (Absatzprognose) kurz illustriert.

Suggested Citation

  • Manfred Deistler & Klaus Neusser, 2004. "Prognose uni- und multivariater Zeitreihen," Diskussionsschriften dp0401, Universitaet Bern, Departement Volkswirtschaft.
  • Handle: RePEc:ube:dpvwib:dp0401

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    References listed on IDEAS

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    More about this item


    Prognose; Identifikation; ARMAX-Systeme;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods


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