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Econophysics Approaches to Large-Scale Business Data and Financial Crisis pp 211–225Cite as

Data Centric Science for Information Society

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Abstract

Due to rapid development of information and communication technologies, the methodology of scientific research and the society itself are changing. The present grand challenge is the development of the cyber-enabled methodology for scientific researches to create knowledge based on large scale massive data. To realize this, it is necessary to develop a method of integrating various types of information. Thus the Bayes modeling becomes the key technology. In the latter half of the paper, we focus on time series and present general state-space model and related recursive filtering algorithms. Several examples are presented to show the usefulness of the general state-space model.

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Author information

Authors and Affiliations

  1. The Institute of Statistical Mathematics, Research Organization of Information and Systems, 10-3 Midori-cho, Tachikawa, Tokyo, 190-8562, Japan

    Genshiro Kitagawa

Authors
  1. Genshiro Kitagawa
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Corresponding author

Correspondence to Genshiro Kitagawa .

Editor information

Editors and Affiliations

  1. Department of Computational, Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama, 226-8502, Japan

    Misako Takayasu (Associate Professor) (Associate Professor)

  2. Research Center for Price Dynamics and Institute of Economic Research, Hitotsubashi University, 2-1 Naka, Kunitachi, Tokyo, 186-8603, Japan

    Tsutomu Watanabe (Professor) (Professor)

  3. Fundamental Research Group, Sony Computer Science Laboratories, 3-14-13 Higashigotanda, Shinagawa-ku, Tokyo, 141-0022, Japan

    Hideki Takayasu (Senior Researcher) (Senior Researcher)

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Kitagawa, G. (2010). Data Centric Science for Information Society. In: Takayasu, M., Watanabe, T., Takayasu, H. (eds) Econophysics Approaches to Large-Scale Business Data and Financial Crisis. Springer, Tokyo. https://doi.org/10.1007/978-4-431-53853-0_11

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