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Long-Memory Processes

  • Paul S.P. Cowpertwait
  • Andrew V. Metcalfe
Chapter
Part of the Use R book series (USE R)

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.

Keywords

Time Series Federal Reserve GARCH Model Packet Arrival Loan Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York 2009

Authors and Affiliations

  1. 1.Inst. Information and Mathematical Sciences, Maasey UniversityAuckland, Albany CampusNew Zealand
  2. 2.School of Mathematical Sciences, University of AdelaideAustralia

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