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Open AccessJournal ArticleDOI

Fractal-Dimensional Properties of Subordinators

Adam Barker
- 01 Sep 2019 - 
- Vol. 32, Iss: 3, pp 1202-1219
TLDR
In this paper, the authors studied the box-counting dimension of sets related to subordinators (non-decreasing Levy processes) and proved a central limit theorem for this dimension.
Abstract
This work looks at the box-counting dimension of sets related to subordinators (non-decreasing Levy processes). It was recently shown in Savov (Electron Commun Probab 19:1–10, 2014) that almost surely $$\lim _{\delta \rightarrow 0}U(\delta )N(t,\delta ) = t$$ , where $$N(t,\delta )$$ is the minimal number of boxes of size at most $$ \delta $$ needed to cover a subordinator’s range up to time t, and $$U(\delta )$$ is the subordinator’s renewal function. Our main result is a central limit theorem (CLT) for $$N(t,\delta )$$ , complementing and refining work in Savov (2014). Box-counting dimension is defined in terms of $$N(t,\delta )$$ , but for subordinators we prove that it can also be defined using a new process obtained by shortening the original subordinator’s jumps of size greater than $$\delta $$ . This new process can be manipulated with remarkable ease in comparison with $$N(t,\delta )$$ , and allows better understanding of the box-counting dimension of a subordinator’s range in terms of its Levy measure, improving upon Savov (2014, Corollary 1). Further, we shall prove corresponding CLT and almost sure convergence results for the new process.

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Journal ArticleDOI

Transience and Recurrence of Markov Processeswith Constrained Local Time

TL;DR: In this paper, the authors studied a class of Markov processes conditioned so that their local time must grow slower than a prescribed function, and they derived necessary and sufficient conditions for transience or recurrence of the conditioned Markov process.
DissertationDOI

Path properties of levy processes

Adam Barker
TL;DR: In this article, the authors consider the problem of determining the distribution of the inverse local time of a Markov process conditioned to remain above a given function, which is a necessary and sufficient condition for transience or recurrence of the process.
Posted Content

Transience and Recurrence of Markov Processes with Constrained Local Time

Adam Barker
- 15 Jun 2018 - 
TL;DR: In this article, the authors study Markov processes conditioned so that their local time must grow slower than a prescribed function, and derive necessary and sufficient conditions for transience or recurrence of the conditioned Markov process.
References
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Book

Fractal Geometry: Mathematical Foundations and Applications

TL;DR: In this article, a mathematical background of Hausdorff measure and dimension alternative definitions of dimension techniques for calculating dimensions local structure of fractals projections of fractality products of fractal intersections of fractalities.
Book

Foundations of modern probability

TL;DR: In this article, the authors discuss the relationship between Markov Processes and Ergodic properties of Markov processes and their relation with PDEs and potential theory. But their main focus is on the convergence of random processes, measures, and sets.
Book

Introductory Lectures on Fluctuations of Lévy Processes with Applications

TL;DR: In this paper, the authors present decompositions of the paths of Levy processes in terms of their local maxima and an understanding of their short-and long-term behaviour.
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