Variable Step Random Walks and Self-Similar Distributions*


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Abstract

We study a scenario under which variable step random walks give anomalous statistics. We begin by analyzing the Martingale Central Limit Theorem to find a sufficient condition for the limit distribution to be non-Gaussian. We study the case when the scaling indexζ is 1/2. For corresponding continuous time processes, it is shown that the probability density function W(x;t) satisfies the Fokker-Planck equation. Possible forms for the diffusion coefficient are given, and related to W(x,t). Finally, we show how a time-series can be used to distinguish between these variable diffusion processes and Lévy dynamics.

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