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A Guide to State Space Modeling of Multiple Time Series

  • Arthur Havenner
Conference paper
Part of the Lecture Notes in Statistics book series (LNS, volume 119)

Abstract

In teaching time series analysis over the past several years I have become aware of the gap between the often elegant theory of the methods developed and the sometimes crude issues that arise in their application to real problems. A substantial amount of important practical information is relegated to a minor position and is either haphazardly conveyed in long sessions in the computer laboratory, or not at all. This guide is an attempt to organize and formalize that information as it applies to the use of Aoki’s state space time series procedure, employing monthly data on four macroeconomic series as an illustration. Here I am taking the role of the expert witness, and offering opinions where relevant; the judgmental decisions embodied in the discussion reflect my experience, both from my own personal projects and from those of my students.

Keywords

Root Mean Square Error Unit Root Time Series Model State Space Model Mean Absolute Percentage Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1997

Authors and Affiliations

  • Arthur Havenner
    • 1
  1. 1.University of CaliforniaDavisUSA

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