Some time series exhibit marked correlations at high lags, and they are referred to as long-memory processes. Long-memory is a feature of many geophysical time series. Flows in the Nile River have correlations at high lags, and Hurst (1951) demonstrated that this affected the optimal design capacity of a dam. Mudelsee (2007) shows that long-memory is a hydrological property that can lead to prolonged drought or temporal clustering of extreme floods. At a rather different scale, Leland et al. (1993) found that Ethernet local area network (LAN) traffic appears to be statistically self-similar and a long-memory process. They showed that the nature of congestion produced by self-similar traffic differs drastically from that predicted by the traffic models used at that time.
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© 2009 Springer-Verlag New York
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Cowpertwait, P.S., Metcalfe, A.V. (2009). Long-Memory Processes. In: Introductory Time Series with R. Use R. Springer, New York, NY. https://doi.org/10.1007/978-0-387-88698-5_8
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DOI: https://doi.org/10.1007/978-0-387-88698-5_8
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