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An algorithm for estimating parameters of state-space models

Author

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  • Wu, Lilian Shiao-Yen
  • Pai, Jeffrey S.
  • Hosking, J.R.M.
Abstract
We describe an algorithm for estimating the parameters of time-series models expressed in state-space form. The algorithm is based on the EM algorithm, and generalizes an algorithm given by Shumway and Stoffer (1982)

Suggested Citation

  • Wu, Lilian Shiao-Yen & Pai, Jeffrey S. & Hosking, J.R.M., 1996. "An algorithm for estimating parameters of state-space models," Statistics & Probability Letters, Elsevier, vol. 28(2), pages 99-106, June.
    • Handle: RePEc:eee:stapro:v:28:y:1996:i:2:p:99-106
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    References listed on IDEAS

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    1. R. H. Shumway & D. S. Stoffer, 1982. "An Approach To Time Series Smoothing And Forecasting Using The Em Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(4), pages 253-264, July.
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    Cited by:

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    2. Romain Houssa & Lasse Bork & Hans Dewachter, 2008. "Identification of Macroeconomic Factors in Large Panels," Working Papers 1010, University of Namur, Department of Economics.
    3. Rainer Schulz & Hizir Sofyan & Axel Werwatz & Rodrigo Witzel, 2003. "Online Prediction of Berlin Single-Family House Prices," Computational Statistics, Springer, vol. 18(3), pages 449-462, September.
    4. Bork, Lasse, 2009. "Estimating US Monetary Policy Shocks Using a Factor-Augmented Vector Autoregression: An EM Algorithm Approach," Finance Research Group Working Papers F-2009-03, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    5. Giuseppe Storti & Cosimo Vitale, 2003. "BL-GARCH models and asymmetries in volatility," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 12(1), pages 19-39, February.
    6. García-Martos, Carolina & Rodríguez, Julio & Sánchez, María Jesús, 2008. "Seasonal dynamic factor analysis and bootstrap inference : application to electricity market forecasting," DES - Working Papers. Statistics and Econometrics. WS ws081406, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Venter, J.H. & de Jongh, P.J., 2014. "Extended stochastic volatility models incorporating realised measures," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 687-707.
    8. Schulz, Rainer & Werwatz, Axel, 2001. "A state space model for Berlin house prices," SFB 373 Discussion Papers 2001,58, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Alessandra Amendola & Giuseppe Storti, 2002. "A non-linear time series approach to modelling asymmetry in stock market indexes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(2), pages 201-216, June.

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