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Fitting and Smoothing Properties of Length Constrained Smoothers Applied to Time Series

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Between Data Science and Applied Data Analysis

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Abstract

We study the fitting and smoothing properties of several non parametric smoothers restricted to be all of the same length for the trend-cycle (signal) estimation of time series. The fitting property is evaluated in terms of the mean square error (MSE), and that of smoothing in terms of the sum of squares of the third differences of the predicted values. These properties are studied for each symmetric (applied to central observations) and asymmetric (for the most recent data point) smoother. The analysis is done on the basis of the results obtained on a large sample of simulated and real-life time series (adjusted for seasonality) characterized by different degrees of signal-noise ratio.

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Author information

Authors and Affiliations

  1. Department of Statistics, University of Bologna, Italy

    Estela Bee Dagum & Alessandra Luati

Authors
  1. Estela Bee Dagum
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  2. Alessandra Luati
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Editor information

Editors and Affiliations

  1. Department of Information Systems, University of Mannheim, Schloss, 68131, Mannheim, Germany

    Martin Schader

  2. Institute of Decision Theory, University of Karlsruhe, Kaiserstr. 12, 76128, Karlsruhe, Germany

    Wolfgang Gaul

  3. Department of Statistics, University of Rome, Piazzale Aldo Moro, 00185, Rome, Italy

    Maurizio Vichi

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© 2003 Springer-Verlag Berlin Heidelberg

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Dagum, E.B., Luati, A. (2003). Fitting and Smoothing Properties of Length Constrained Smoothers Applied to Time Series. In: Schader, M., Gaul, W., Vichi, M. (eds) Between Data Science and Applied Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18991-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-18991-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40354-8

  • Online ISBN: 978-3-642-18991-3

  • eBook Packages: Springer Book Archive

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