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Wavelet methods for time series analysis Andrew T. Walden, Donald B. Percival
Publisher: Cambridge University Press

The OCW Finder Wavelets, Filter Banks and Applications, Spring 2003. . I generated 500 white-noise data series with the same time sampling as the Agassiz d18O data from 6000 to 8000 yr BP. [9] introduced a new method to describe dynamic patterns of the real exchange rate comovements time series and to analyze their influence in currency crises. Mit civil mit foreign languages literatures. Then I computed the strength of the strongest peak in the DCDFT spectrum over the I also analyzed the GISP2 d18O data using another popular time-frequency method, wavelet analysis (using the WWZ, Foster 1996, Astronomical J., 112, 1709). That is to say that, the cluster labels of switching series are varied over time. D'Urso and Maharaj [1, 2] pointed out the existence of switching time series and studied it by autocorrelation-based and wavelets-based methods, respectively. Y Zhou, JAD Aston Modeling trigonometric seasonal components for monthly economic time series, Applied Economics, in press. Pharmacokinetic modelling of the anti-malarial drug artesunate and its active metabolite dihydroartemisinin, Computer Methods and Programs in Biomedicine, in press. Quantifying uncertainty in change points (2012), Journal of Time Series Analysis, 33:807-823. Topics in Combinatorial Optimization, Spring 2004. Topics in Brain and Cognitive Sciences Human Ethology, Spring 2001. Time Series Analysis, Fall 2002.