Time-dependent spectral analysis of epidemiological time-series with wavelets

By Bernard Cazelles, Mario Chavez, Guillaume Constantin de Magny, J. Guégan, Simon Hales. Journal of the Royal Society Interface, 2007

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THE CONTINUOUS WAVELET TRANSFORM: MOVING BEYOND UNI‐ AND BIVARIATE ANALYSIS (2014, neutral): “The conversion of scales to frequencies is based on the energy frequency !E , given by (11), i.”
The continuous wavelet transform : a primer (2011, neutral): “by convolution with appropriate windows; see Cazelles, Chavez, de Magny, Guégan and Hales [7] or Grinsted, Moore and Jevrejeva [24], for details.”
Using wavelets to decompose the time–frequency effects of monetary policy (2008, methodology): “[25,4, 5 ] and define the wavelet coherency between two time series x ={ xn} and y ={ yn} as follows:”
Nonlinear impacts of climatic variability on the density‐dependent regulation of an insect vector of disease (2012, methodology): “, changing through time) between climatic variability and mosquito time series using cross-wavelet analysis (Chaves & Pascual, 2006; Cazelles et al., 2007).”
Oil and the macroeconomy: using wavelets to analyze old issues (2011, methodology): “Following Jevrejeva et al. (2003), Bloomfield et al. (2004), and Cazelles et al. (2007), three tools are utilized: the wavelet power spectrum, wavelet coherency and wavelet phase-difference.”