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Analysing multiple time series and extending significance testing in wavelet analysis ArchiMer
Rouyer, Tristan; Fromentin, Jean-marc; Stenseth, N; Cazelles, B.
In nature, non-stationarity is rather typical, but the number of statistical tools allowing for non-stationarity remains rather limited. Wavelet analysis is such a tool allowing for non-stationarity but the lack of an appropriate test for statistical inference as well as the difficulty to deal with multiple time series are 2 important shortcomings that limits its use in ecology. We present 2 approaches to deal with these shortcomings. First, we used 1/f beta models to test cycles in the wavelet spectrum against a null hypothesis that takes into account the highly autocorrelated nature of ecological time series. To illustrate the approach, we investigated the fluctuations in bluefin tuna trap catches with a set of different null models. The 1/f beta models...
Tipo: Text Palavras-chave: Maximum covariance analysis; Surrogates; Wavelet significance testing; Wavelet clustering; Multivariate time series; Non stationarity.
Ano: 2008 URL: http://archimer.ifremer.fr/doc/2008/publication-4291.pdf
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