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State Space Modeling of Time Series

In: Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach

Author

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  • Genshiro Kitagawa

    (The Institute of Statistical Mathematics)

Abstract

Summary The state space model method for time series analysis is shown in this paper. Most of the standard time series models such as the AR or ARMA models can be expressed by the state space model. Further, various types of constraints on the parameter of the model can be conveniently incorporated in the state space model. Therefore, various types of nonstationary time series models can be handled by using the state space model.

Suggested Citation

  • Genshiro Kitagawa, 1994. "State Space Modeling of Time Series," Springer Books, in: H. Bozdogan & S. L. Sclove & A. K. Gupta & D. Haughton & G. Kitagawa & T. Ozaki & K. Tanabe (ed.), Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach, chapter 3, pages 43-62, Springer.
    • Handle: RePEc:spr:sprchp:978-94-011-0866-9_4
    DOI: 10.1007/978-94-011-0866-9_4
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