Finite iterative forecasting model based on fractional generalized pareto motion

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SUMMARY

    This paper studies the infinite variance prediction model for random sequences with LRD characteristics. This paper introduces a three-parameter generalized Pareto distribution to simulate infinite variance processes. The authors use the generalized Pareto distribution (GPD) to model infinite variance processes, by focusing only on the case of the tail parameter α ∈. Compared with fractional Brownian motion, describing LRD by a self-similar parameter H, the LRD of the fGPm is determined by the tail parameter α and the self-similar parameter H, so that the fGPm can describe the LRD process in a more flexible . . .

     

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