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Time-Varying Parameters Prediction

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  • Carlo Grillenzoni

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  • Carlo Grillenzoni, 2000. "Time-Varying Parameters Prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(1), pages 108-122, March.
    • Handle: RePEc:spr:aistmt:v:52:y:2000:i:1:p:108-122
    DOI: 10.1023/A:1004189000171
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    References listed on IDEAS

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    1. Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, vol. 26(3), pages 271-281, December.
    2. Tjøstheim, Dag, 1986. "Estimation in nonlinear time series models," Stochastic Processes and their Applications, Elsevier, vol. 21(2), pages 251-273, February.
    3. Pagan, Adrian, 1980. "Some identification and estimation results for regression models with stochastically varying coefficients," Journal of Econometrics, Elsevier, vol. 13(3), pages 341-363, August.
    4. Grillenzoni, Carlo, 1993. "ARIMA Processes with ARIMA Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 235-250, April.
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    Cited by:

    1. Karanasos, Menelaos & Paraskevopoulos,Alexandros & Canepa, Alessandra, 2020. "Unified Theory for the Large Family of Time Varying Models with Arma Representations: One Solution Fits All," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202008, University of Turin.
    2. Sánchez, Ismael, 2002. "Recursive estimation o dynamic models using cook's distance,with application to wind energy orecast," DES - Working Papers. Statistics and Econometrics. WS ws025515, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Karanasos, Menelaos & Paraskevopoulos, Alexandros & Magdalinos, Anastasios & Canepa, Alessandra, 2024. "A Unified Theory for Arma Models with Varying Coefficients: One Solution Fits All," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202413, University of Turin.

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