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Trend Estimation

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International Encyclopedia of Statistical Science

Trend estimation deals with the characterization of the underlying, or long–run, evolution of a time series. Despite being a very pervasive theme in time series analysis since its inception, it still raises a lot of controversies. The difficulties, or better, the challenges, lie in the identification of the sources of the trend dynamics, and in the definition of the time horizon which defines the long run. The prevalent view in the literature considers the trend as a genuinely latent component, i.e., as the component of the evolution of a series that is persistent and cannot be ascribed to observable factors. As a matter of fact, the univariate approaches reviewed here assume that the trend is either a deterministic or random function of time.

A variety of approaches is available, which can be classified as nonparametric (kernel methods, local polynomial regression, band-pass filters, and wavelet multiresolution analysis), semiparametric (splines and Gaussian random fields) and...

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Author information

Authors and Affiliations

  1. University of Rome “Tor Vergata”, Rome, Italy

    Tommaso Proietti

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  1. Tommaso Proietti
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Editor information

Editors and Affiliations

  1. Department of Statistics and Informatics, Faculty of Economics, University of Kragujevac, City of Kragujevac, Serbia

    Miodrag Lovric

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© 2011 Springer-Verlag Berlin Heidelberg

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Proietti, T. (2011). Trend Estimation. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_598

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