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Emergence of Heavy-Tailed Distributions in a Random Multiplicative Model Driven by a Gaussian Stochastic Process

机译:高斯随机过程驱动的随机乘法模型中重尾分布的出现

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We consider a random multiplicative stochastic process with multipliers given by the exponential of a Brownian motion. The positive integer moments of the distribution function can be computed exactly, and can be represented as the grand partition function of an equivalent lattice gas with attractive 2-body interactions. The numerical results for the positive integer moments display a sharp transition at a critical value of the model parameters, which corresponds to a phase transition in the equivalent lattice gas model. The shape of the terminal distribution changes suddenly at the critical point to a heavy-tailed distribution. The transition can be related to the position of the complex zeros of the grand partition function of the lattice gas, in analogy with the Lee, Yang picture of phase transitions in statistical mechanics. We study the properties of the equivalent lattice gas in the thermodynamical limit, which corresponds to the continuous time limit of the random multiplicative model, and derive the asymptotics of the approach to the continuous time limit. The results can be generalized to a wider class of random multiplicative processes, driven by the exponential of a Gaussian stochastic process.
机译:我们考虑一个由布朗运动指数给定的乘数的随机乘法随机过程。分布函数的正整数矩可以精确计算,并且可以表示为具有有吸引力的2体相互作用的等效晶格气的大分配函数。正整数矩的数值结果在模型参数的临界值处显示出急剧的转变,这与等效晶格气体模型中的相变相对应。终端分布的形状在临界点突然变为重尾分布。与统计力学中的相变的Lee,Yang图像类似,该跃迁可以与晶格气体大分配函数的复零位置相关。我们研究了在热力学极限(相当于随机乘法模型的连续时间极限)中的等效晶格气的性质,并推导了达到连续时间极限的渐近性。在高斯随机过程的指数驱动下,结果可以推广到更广泛的一类随机乘法过程。

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