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

Than the previous methods, the error is actually roughly the same as for all other options we tried out. Insightful has released the following time series packages via CSAN at http://csan.insightful.com: FRACTAL: stochastic fractal time series and nonlinear modeling. The complexity of the system is expressed by several parameters of nonlinear dynamics, such as embedding dimension or false nearest neighbors, and the method of delay coordinates is applied to the time series. This is a software package for the analysis of a data series using wavelet methods. In this way, any sudden event in a time series can be determined to reasonable accuracy through the wavelet method, regardless of any particular frequency that may be associated with the phenomenon. Fig 3: Wavelet analysis of the stalagmite time series. We also fit Finally, we find that a series of damped random walk models provides a good fit to the 10Be data with a fixed characteristic time scale of 1000 years, which is roughly consistent with the quasi-periods found by the Fourier and wavelet analyses. The normal reaction of the bureaucrat is to try and discredit the independent research by using the same techniques that we often see here. WMTSA: wavelet methods for time series analysis. Wavelet analysis techniques, while not as commonly understood as Fourier analysis, are nonetheless frequently applied to problems in which time and frequency information are desired simultaneously.