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Zbl 1051.93095
Li, Ming; Chi, Chi-Hung
A correlation-based computational model for synthesizing long-range dependent data. (English)
[J] J. Franklin Inst. 340, No. 6-7, 503-514 (2003). ISSN 0016-0032; ISSN 1879-2693/e

A second-order stationary random function $x(t)$ is called a stationary process with long-range dependent (LRD) data if $$r_x(t)= E[x(t) x(t+\tau)]\sim c\tau^{2H- 2}\,(\tau\to \infty),\ H\in (0.5, 1),$$ where $c> 0$; the parameter $H$ is called the Hurst parameter. The authors present a computation model to generate LRD data according to a given correlation structure by filtering white noise.
[Grigori Milstein (Ekaterinburg)]

MSC 2000:: *93E03 General theory of stochastic systems
60G15 Gaussian processes
60G10 Stationary processes

Keywords: Long-range dependent data generation; Brownian motion; Fractional Gaussian noise; Filters; Fourier analysis; Teletraffic; Stationary process; Hurst parameter

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