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A correlation-based computational model for synthesizing long-range dependent data. (English) Zbl 1051.93095
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.

MSC:
93E03General theory of stochastic systems
60G15Gaussian processes
60G10Stationary processes
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References:
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