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Flexible least squares estimation of state space models: an alternative to Kalman-filtering

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  • Kladroba, Andreas

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  • Kladroba, Andreas, 2005. "Flexible least squares estimation of state space models: an alternative to Kalman-filtering," IBES Diskussionsbeiträge 149, University of Duisburg-Essen, Institute of Business and Economic Studie (IBES).
    • Handle: RePEc:zbw:udewwd:149
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    Cited by:

    1. Matthew J. Lebo & Janet M. Box‐Steffensmeier, 2008. "Dynamic Conditional Correlations in Political Science," American Journal of Political Science, John Wiley & Sons, vol. 52(3), pages 688-704, July.
    2. Claudio Morana, 2009. "An omnibus noise filter," Computational Statistics, Springer, vol. 24(3), pages 459-479, August.
    3. Zhou, Jian, 2013. "Conditional market beta for REITs: A comparison of modeling techniques," Economic Modelling, Elsevier, vol. 30(C), pages 196-204.
    4. A. Talha Yalta, 2016. "Bootstrap Inference of Level Relationships in the Presence of Serially Correlated Errors: A Large Scale Simulation Study and an Application in Energy Demand," Computational Economics, Springer;Society for Computational Economics, vol. 48(2), pages 339-366, August.
    5. Kuethe, Todd H. & Foster, Kenneth A. & Florax, Raymond J.G.M., 2008. "A Spatial Hedonic Model with Time-Varying Parameters: A New Method Using Flexible Least Squares," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6306, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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