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Estimating the system order by subspace methods

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  • Alfredo García-Hiernaux

    ()

  • José Casals
  • Miguel Jerez

Abstract

This paper discusses how to specify the order of a state-space model. To do so, we start by revising existing approaches and find in them two basic shortcomings: (i) some of them have a poor performance in short samples and (ii) most of them are not robust, meaning that their performance critically depends on the data generating process. We tackle these two issues by proposing new and refined criteria. Monte Carlo simulations provide evidence of the potential of the proposals. Copyright Springer-Verlag 2012

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File URL: http://hdl.handle.net/10.1007/s00180-011-0264-2
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Bibliographic Info

Article provided by Springer in its journal Computational Statistics.

Volume (Year): 27 (2012)
Issue (Month): 3 (September)
Pages: 411-425

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Handle: RePEc:spr:compst:v:27:y:2012:i:3:p:411-425

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Related research

Keywords: Information criteria; State-space models; Subspace methods; System order; C32; C51; C52;

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References

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  1. Bujosa, Marcos & Garcia-Ferrer, Antonio & Young, Peter C., 2007. "Linear dynamic harmonic regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 999-1024, October.
  2. Bauer, Dietmar, 2005. "Estimating Linear Dynamical Systems Using Subspace Methods," Econometric Theory, Cambridge University Press, vol. 21(01), pages 181-211, February.
  3. Jesus Gonzalo & Jean-Yves Pitarakis, 2001. "Lag Length Estimation in Large Dimensional Systems," Econometrics 0108003, EconWPA.
  4. Bengtsson, Thomas & Cavanaugh, Joseph E., 2006. "An improved Akaike information criterion for state-space model selection," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2635-2654, June.
  5. Carl Eckart & Gale Young, 1936. "The approximation of one matrix by another of lower rank," Psychometrika, Springer, vol. 1(3), pages 211-218, September.
  6. Casals, Jose & Sotoca, Sonia & Jerez, Miguel, 1999. "A fast and stable method to compute the likelihood of time invariant state-space models," Economics Letters, Elsevier, vol. 65(3), pages 329-337, December.
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Cited by:
  1. Alfredo García‐Hiernaux, 2011. "Forecasting linear dynamical systems using subspace methods," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(5), pages 462-468, 09.

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