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A power-law model and other models for long-range dependence

Part of: Stochastic processes Inference from stochastic processes

Published online by Cambridge University Press:  14 July 2016

R. J. Martin  and
A. M. Walker
R. J. Martin*
Affiliation:
University of Sheffield
A. M. Walker*
Affiliation:
University of Sheffield
*
∗Postal address: School of Mathematics and Statistics, The University of Sheffield, Sheffield S3 7RH, UK.
∗Postal address: School of Mathematics and Statistics, The University of Sheffield, Sheffield S3 7RH, UK.
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Abstract

It is becoming increasingly recognized that some long series of data can be adequately and parsimoniously modelled by stationary processes with long-range dependence. Some new discrete-time models for long-range dependence or slow decay, defined by their correlation structures, are discussed. The exact power-law correlation structure is examined in detail.

Keywords

LONG MEMORYPERSISTENCESLOW DECAY

MSC classification

Primary: 62M10: Time series, auto-correlation, regression, etc.
Secondary: 60G10: Stationary processes 60G18: Self-similar processes
Type
Research Papers
Information
Journal of Applied Probability , Volume 34 , Issue 3 , September 1997 , pp. 657 - 670
Copyright
Copyright © Applied Probability Trust 1997 

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