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Origins and Generation of Long Memory

In: Long-Memory Processes

Author

Listed:
  • Jan Beran

    (University of Konstanz, Dept. of Mathematics and Statistics)

  • Yuanhua Feng

    (University of Paderborn, Faculty of Business Administration and Economics)

  • Sucharita Ghosh

    (Swiss Federal Research Institute WSL)

  • Rafal Kulik

    (University of Ottawa, Dept. of Mathematics and Statistics)

Abstract

In this chapter we discuss typical methods for constructing long-memory processes. Many models are motivated by probabilistic and statistical principles. On the other hand, sometimes one prefers to be lead by subject specific considerations. Typical for the first approach is the definition of linear processes with long memory, or fractional ARIMA models. Subject specific models have been developed for instance in physics, finance and network engineering. Often the occurrence of long memory is detected by nonspecific, purely statistical methods, and subject specific models are then developed to explain the phenomenon. For example, in economics aggregation is a possible reason for long-range dependence, in computer networks long memory may be due to certain distributional properties of interarrival times. Often long memory is also linked to fractal structures.

Suggested Citation

  • Jan Beran & Yuanhua Feng & Sucharita Ghosh & Rafal Kulik, 2013. "Origins and Generation of Long Memory," Springer Books, in: Long-Memory Processes, edition 127, chapter 0, pages 43-106, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-35512-7_2
    DOI: 10.1007/978-3-642-35512-7_2
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