Identification and characterization of water quality transients using wavelet analysis. I. Wavelet analysis methodology

Dohan, Kathleen; Whitfield, Paul H.

doi:10.1016/s0273-1223(97)00490-3

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Cited by 10 publications

(1 citation statement)

References 15 publications

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“…In this work, both Daubechies and Morlet wavelets are used. The Daubechies family offers a compromise between smoothness and compactness (Dohan and Whitfield 1997). Its soft signal variations and shape allow for an easy fit to our type of data.…”

Section: Mother Waveletsmentioning

confidence: 99%

Assessment of CO2 dynamics in subsurface atmospheres using the wavelet approach: from cavity–atmosphere exchange to anthropogenic impacts in Rull cave (Vall d′Ebo, Spain)

et al. 2016

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Section: Mother Waveletsmentioning

confidence: 99%

Assessment of CO2 dynamics in subsurface atmospheres using the wavelet approach: from cavity–atmosphere exchange to anthropogenic impacts in Rull cave (Vall d′Ebo, Spain)

et al. 2016

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Optimal Multi-scale Time Series Decomposition for Financial Forecasting Using Wavelet Thresholding Techniques

Shin¹,

Han²

1999

Lecture Notes in Computer Science

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A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis

Rodríguez-Arias

Rodó

2004

Oecologia

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Here we describe a practical, step-by-step primer to scale-dependent correlation (SDC) analysis. The analysis of transitory processes is an important but often neglected topic in ecological studies because only a few statistical techniques appear to detect temporary features accurately enough. We introduce here the SDC analysis, a statistical and graphical method to study transitory processes at any temporal or spatial scale. SDC analysis, thanks to the combination of conventional procedures and simple well-known statistical techniques, becomes an improved time-domain analogue of wavelet analysis. We use several simple synthetic series to describe the method, a more complex example, full of transitory features, to compare SDC and wavelet analysis, and finally we analyze some selected ecological series to illustrate the methodology. The SDC analysis of time series of copepod abundances in the North Sea indicates that ENSO primarily is the main climatic driver of short-term changes in population dynamics. SDC also uncovers some long-term, unexpected features in the population. Similarly, the SDC analysis of Nicholson's blowflies data locates where the proposed models fail and provides new insights about the mechanism that drives the apparent vanishing of the population cycle during the second half of the series.

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Identification and characterization of water quality transients using wavelet analysis. I. Wavelet analysis methodology

Cited by 10 publications

References 15 publications

Assessment of CO2 dynamics in subsurface atmospheres using the wavelet approach: from cavity–atmosphere exchange to anthropogenic impacts in Rull cave (Vall d′Ebo, Spain)

Assessment of CO2 dynamics in subsurface atmospheres using the wavelet approach: from cavity–atmosphere exchange to anthropogenic impacts in Rull cave (Vall d′Ebo, Spain)

Optimal Multi-scale Time Series Decomposition for Financial Forecasting Using Wavelet Thresholding Techniques

A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis

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