Wavelet Analysis of Seasonal Long Memory
نویسنده
چکیده
The analysis of time series with slowly decaying autocovariances, usually called long-memory processes, has been extensively studied over the past decade. Time series with slowly decaying periodic autocovariances have caught only limited attention recently. We investigate the ability of wavelet transforms, speciically the discrete wavelet packet transform, to analyze and adequately estimate parameters of interest in the case of seasonal long memory. We apply our methodology to atmospheric CO2 measurements collected at the Mauna Loa observatory.
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