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Signal Extraction and Knowledge Discovery Based on Statistical Modeling

  • Genshiro Kitagawa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2842)

Abstract

In the coming post IT era, the problems of signal extraction and knowledge discovery from huge data sets will become very important. For this problem, the use of good model is crucial and thus the statistical modeling will play an important role. In this paper, we show two basic tools for statistical modeling, namely the information criteria for the evaluation of the statistical models and generic state space model which provides us with a very flexible tool for modeling complex and time-varying systems. As examples of these methods we shall show some applications in seismology and macro economics.

Keywords

State Space Model Signal Extraction Asymptotic Bias Macro Economic Augmented State Vector 
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 Berlin Heidelberg 2003

Authors and Affiliations

  • Genshiro Kitagawa
    • 1
  1. 1.The Institute of Statistical MathematicsTokyoJapan

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