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Extensions of the Forward Search to Time Series

Author

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  • Riani Marco

    (University of Parma)

Abstract

This paper extends the forward search technique to the analysis of structural time series data. It provides a series of powerful new forward plots that use information from the whole sample to display the effect of each observation on a wide variety of aspects of the fitted model and shows how the forward search, free from masking and swamping problems, can detect the main underlying features of the series under study (masked multiple outliers, level shifts or transitory changes). The effectiveness of the suggested approach is shown through the analysis of real and simulated data.

Suggested Citation

  • Riani Marco, 2004. "Extensions of the Forward Search to Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-25, May.
    • Handle: RePEc:bpj:sndecm:v:8:y:2004:i:2:n:2
    DOI: 10.2202/1558-3708.1208
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    References listed on IDEAS

    as
    1. Anthony C. Atkinson, 2002. "Forward search added-variable t-tests and the effect of masked outliers on model selection," Biometrika, Biometrika Trust, vol. 89(4), pages 939-946, December.
    2. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, December.
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    Cited by:

    1. Lisa Crosato & Luigi Grossi, 2019. "Correcting outliers in GARCH models: a weighted forward approach," Statistical Papers, Springer, vol. 60(6), pages 1939-1970, December.
    2. Proietti, Tommaso & Riani, Marco, 2007. "Transformations and Seasonal Adjustment: Analytic Solutions and Case Studies," MPRA Paper 7862, University Library of Munich, Germany.
    3. Tommaso Proietti & Marco Riani, 2009. "Transformations and seasonal adjustment," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 47-69, January.
    4. Bellini, Tiziano & Riani, Marco, 2012. "Robust analysis of default intensity," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3276-3285.
    5. L. Grossi & G. Morelli, 2006. "Robust volatility forecasts and model selection in financial time series," Economics Department Working Papers 2006-SE02, Department of Economics, Parma University (Italy).

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