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Wiener Kolmogorov Filtering, Frequency-Selective Filtering, And Polynomial Regression

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  • Pollock, D.S.G.

Abstract

Adaptations of the classical Wiener Kolmogorov filters are described that enable them to be applied to short nonstationary sequences. Alternative filtering methods that operate in the time domain and the frequency domain are described. The frequency-domain methods have the advantage of allowing components of the data to be separated along sharp dividing lines in the frequency domain, without incurring any leakage. The paper contains a novel treatment of the start-up problem that affects the filtering of trended data sequences.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 23 (2007)
Issue (Month): 01 (February)
Pages: 71-88

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Handle: RePEc:cup:etheor:v:23:y:2007:i:01:p:71-88_07

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Cited by:
  1. D.S.G. Pollock, 2008. "IDEOLOG: A Program for Filtering Econometric Data - A Synopsis of Alternative Methods," Discussion Papers in Economics 08/21, Department of Economics, University of Leicester.
  2. Macaro, Christian, 2010. "Bayesian non-parametric signal extraction for Gaussian time series," Journal of Econometrics, Elsevier, vol. 157(2), pages 381-395, August.
  3. Stephen Pollock, 2014. "Econometric Filters," Discussion Papers in Economics 14/07, Department of Economics, University of Leicester.
  4. Stephen Pollock, 2014. "Trends Cycles and Seasons: Econometric Methods of Signal Extraction," Discussion Papers in Economics 14/04, Department of Economics, University of Leicester.

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