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Extensions of the Forward Search to Time Series

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  • Riani Marco

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    (University of Parma)

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    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.

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    File URL: http://www.degruyter.com/view/j/snde.2004.8.2/snde.2004.8.2.1208/snde.2004.8.2.1208.xml?format=INT
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    Bibliographic Info

    Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

    Volume (Year): 8 (2004)
    Issue (Month): 2 (May)
    Pages: 1-25

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    Handle: RePEc:bpj:sndecm:v:8:y:2004:i:2:n:2

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    Web page: http://www.degruyter.com

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    Web: http://www.degruyter.com/view/j/snde

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    Cited by:
    1. Proietti, Tommaso & Riani, Marco, 2007. "Transformations and Seasonal Adjustment: Analytic Solutions and Case Studies," MPRA Paper 7862, University Library of Munich, Germany.
    2. Bellini, Tiziano & Riani, Marco, 2012. "Robust analysis of default intensity," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3276-3285.
    3. 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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