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Self-stabilizing processes based on random signs

Research output: Contribution to journalArticle

Author(s)

K. J. Falconer, J. Lévy Véhel

School/Research organisations

Abstract

A self-stabilizing processes {Z(t), t ∈ [t0,t1)} is a random process which when localized, that is scaled to a fine limit near a given t ∈ [t0,t1), has the distribution of an α(Z(t))-stable process, where α:ℝ→(0,2) is a given continuous function. Thus the stability index near t depends on the value of the process at t. In an earlier paper we constructed self-stabilizing processes using sums over plane Poisson point processes in the case of α:ℝ→(0,1) which depended on the almost sure absolute convergence of the sums. Here we construct pure jump self-stabilizing processes when α may take values greater than 1 when convergence may no longer be absolute. We do this in two stages, firstly by setting up a process based on a fixed point set but taking random signs of the summands, and then randomizing the point set to get a process with the desired local properties.
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Details

Original languageEnglish
Number of pages19
JournalJournal of Theoretical Probability
VolumeFirst Online
Early online date29 Sep 2018
DOIs
Publication statusE-pub ahead of print - 29 Sep 2018

    Research areas

  • Self-similar process, Stable process, Localisable process, Multistable process, Poisson point process

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