2011
DOI: 10.1029/2011pa002195
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Detecting cycles in stratigraphic data: Spectral analysis in the presence of red noise

Abstract: [1] We discuss the detection of cyclic signals in stratigraphic 'time series' using spectral methods. The dominant source of variance in the stratigraphic record is red noise, which greatly complicates the process of searching for weak periodic signals. We highlight two issues that are more significant than generally appreciated. The first is the lack of a correction for 'multiple tests' -many independent frequencies are examined for periods but using a significance test appropriate for examination of a single… Show more

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Cited by 84 publications
(87 citation statements)
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“…Random, nonperiodic variations in the climate system, such as some of the dynamics associated with ocean circulation or sedimentary depositional processes, are quite common in nature, resulting in apparent periodicities giving rise to a red noise power spectrum (54). This generates a problem of discriminating true periodicities from red noise variation.…”
Section: Orbital Forcing Of Depositionmentioning
confidence: 99%
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“…Random, nonperiodic variations in the climate system, such as some of the dynamics associated with ocean circulation or sedimentary depositional processes, are quite common in nature, resulting in apparent periodicities giving rise to a red noise power spectrum (54). This generates a problem of discriminating true periodicities from red noise variation.…”
Section: Orbital Forcing Of Depositionmentioning
confidence: 99%
“…We also tested our band-pass-filtered data toward a noise model with a bending power-law spectrum noise model (see SI Text for further details). As before, the constants of the noise model were fit by leastsquares error to the median smoothed periodogram (54). We find that the robust red noise model has a smaller least-squares error toward the median smoothed periodogram than the bending power-law spectrum noise model.…”
Section: Orbital Forcing Of Depositionmentioning
confidence: 99%
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“…Efforts are underway to derive techniques for calculating the FAP for a given periodogram in a way that is robust and reliable even for light curves with a significant red-noise component. These techniques are still developing, however, and are often computationally or mathematically complex (Vio et al 2010), or have only been tested with particular types of time-series data (e.g., light curves with power-law spectral indices, including X-ray data for active galaxies or stratigraphic geological data; Vaughan 2010; Vaughan et al 2011).…”
Section: Statistical Tests For Evaluating the Significance Of Candidamentioning
confidence: 99%
“…Despite this progress, critical papers on cyclostratigraphy have been published (e.g. Miall & Miall 2004;Bailey 2009;Vaughan et al 2011) focusing on the following points:…”
mentioning
confidence: 99%