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Prognose uni- und multivariater Zeitreihen

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Author Info
Manfred Deistler
Klaus Neusser

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Abstract

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.

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Paper provided by Universitaet Bern, Departement Volkswirtschaft in its series Diskussionsschriften with number dp0401.

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Date of creation: Jan 2004
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Handle: RePEc:ube:dpvwib:dp0401

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Related research
Keywords: Prognose; Identifikation; ARMAX-Systeme;

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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