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Some Results on 1 Polynomial Trend Filtering

Filters, Waves and Spectra

Department of Economics, University of Leciceter, Leicester LE1 7RH, UK
Econometrics 2018, 6(3), 35;
Received: 17 March 2018 / Revised: 15 July 2018 / Accepted: 17 July 2018 / Published: 27 July 2018
(This article belongs to the Special Issue Filtering)
Econometric analysis requires filtering techniques that are adapted to cater to data sequences that are short and that have strong trends. Whereas the economists have tended to conduct their analyses in the time domain, the engineers have emphasised the frequency domain. This paper places its emphasis in the frequency domain; and it shows how the frequency-domain methods can be adapted to cater to short trended sequences. Working in the frequency domain allows an unrestricted choice to be made of the frequency response of a filter. It also requires that the data should be free of trends. Methods for extracting the trends prior to filtering and for restoring them thereafter are described. View Full-Text
Keywords: time series; Fourier analysis; sampling; filtering time series; Fourier analysis; sampling; filtering
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MDPI and ACS Style

Pollock, D.S.G. Filters, Waves and Spectra. Econometrics 2018, 6, 35.

AMA Style

Pollock DSG. Filters, Waves and Spectra. Econometrics. 2018; 6(3):35.

Chicago/Turabian Style

Pollock, D. Stephen G. 2018. "Filters, Waves and Spectra" Econometrics 6, no. 3: 35.

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