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Mixture Kalman filters

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  • Rong Chen
  • Jun S. Liu
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    Bibliographic Info

    Article provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series B (Methodological).

    Volume (Year): 62 (2000)
    Issue (Month): 3 ()
    Pages: 493-508

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    Handle: RePEc:bla:jorssb:v:62:y:2000:i:3:p:493-508

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    Cited by:
    1. Neil Shephard & Charles S. Bos, 2004. "Inference for adaptive time series models: stochastic volatility and conditionally Gaussian state space form," Economics Series Working Papers 2004-W02, University of Oxford, Department of Economics.
    2. Hammer, Hugo & Tjelmeland, Håkon, 2011. "Approximate forward-backward algorithm for a switching linear Gaussian model," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 154-167, January.
    3. Kim, Hyoung-Moon & Ryu, Duchwan & Mallick, Bani K. & Genton, Marc G., 2014. "Mixtures of skewed Kalman filters," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 228-251.
    4. repec:wyi:journl:002173 is not listed on IDEAS
    5. Drew Creal & Siem Jan Koopman & Eric Zivot, 2010. "Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
    6. Mark Briers & Arnaud Doucet & Simon Maskell, 2010. "Smoothing algorithms for state–space models," Annals of the Institute of Statistical Mathematics, Springer, vol. 62(1), pages 61-89, February.
    7. Nicolas Chopin, 2007. "Dynamic Detection of Change Points in Long Time Series," Annals of the Institute of Statistical Mathematics, Springer, vol. 59(2), pages 349-366, June.
    8. Mark Irwin & Noel Cressie & Gardar Johannesson, 2002. "Spatial-temporal nonlinear filtering based on hierarchical statistical models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 11(2), pages 249-302, December.
    9. Gary Koop & Dimitris Korobilis, 2011. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," Working Papers 1118, University of Strathclyde Business School, Department of Economics.
    10. Creal, D., 2009. "A survey of sequential Monte Carlo methods for economics and finance," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    11. Chopin, N. & Del Moral, P. & Rubenthaler, S., 2011. "Stability of Feynman-Kac formulae with path-dependent potentials," Stochastic Processes and their Applications, Elsevier, vol. 121(1), pages 38-60, January.
    12. Dong Guo & Xiaodong Wang & Rong Chen, 2003. "Nonparametric adaptive detection in fading channels based on sequential Monte Carlo and Bayesian model averaging," Annals of the Institute of Statistical Mathematics, Springer, vol. 55(2), pages 423-436, June.

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