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Improved Frequency-selective Filters

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  • Stephen Pollock

    (Queen Mary, University of London)

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    Abstract

    This paper gives an account of some techniques for designing recursive frequency-selective filters which can be applied to data sequences of limited duration which may be nonstationary. The designs are based on the Wiener-Kolmogorov theory of signal extraction which employs a statistical model of the processes generating the data. The statistical model may be regarded as an heuristic device which is designed with a view to ensuring that the resulting signal-extraction filters have certain preconceived properties.

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    File URL: http://www.econ.qmul.ac.uk/papers/doc/wp449.pdf
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    Bibliographic Info

    Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 449.

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    Date of creation: Dec 2001
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    Handle: RePEc:qmw:qmwecw:wp449

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    Related research

    Keywords: Signal extraction; Linear filtering; Filter design; Trend estimation; Frequency-domain analysis;

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    1. James Morley & Charles Nelson & Eric Zivot, 2002. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Working Papers UWEC-2002-01, University of Washington, Department of Economics.
    2. Gomez, Victor, 1999. "Three Equivalent Methods for Filtering Finite Nonstationary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 109-16, January.
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