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Searches for periodic signals (candidate Milankovitch cycles) in stratigraphic data often make use of methods of spectral analysis, some of which have come to be regarded as standard and therefore reliable. In this paper we highlight a problem with the application of filtering, or smoothing, to the data prior to spectral analysis. Such preprocessing is frequently used to amplify the signal-to-noise ratio at the expected wavelength. Using synthetic random data, we demonstrate how filtering generates artificial spectral peaks close to the characteristic wavelength of the filter. When applying the same preprocessing methods to actual stratigraphic data, we find that...

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