论文标题

扩散过程的无界加性功能的大偏差渐近学

Large deviations asymptotics for unbounded additive functionals of diffusion processes

论文作者

Bazhba, Mihail, Blanchet, Jose, Laeven, Roger J. A., Zwart, Bert

论文摘要

我们研究了一类无界添加功能的大偏差渐近学,这些功能被解释为标准化的累积区域,具有亚线性梯度漂移的一维兰格文鸟扩散。我们的结果提供了有关速度和速率功能的参数见解,从漂移的增长率和添加剂功能的增长率方面。我们在这些生长参数方面发现了一个临界价值,该参数决定了大偏离渐近学的子线性速度区域。我们的方法基于独立兴趣的各种结构,包括在交替的更新周期中对扩散过程的分解以及使用合适的时间和空间尺度对周期中路径进行详细分析。亚线性行为的关键是由单个大型跳跃原理引起的重尾大偏差现象,其结果是在每个再生周期中,扩散过程的累积面积的上尾渐近行为被证明是半表情的(即,重尾weibull类型)。

We study large deviations asymptotics for a class of unbounded additive functionals, interpreted as normalized accumulated areas, of one-dimensional Langevin diffusions with sub-linear gradient drifts. Our results provide parametric insights on the speed and the rate functions in terms of the growth rate of the drift and the growth rate of the additive functional. We find a critical value in terms of these growth parameters that dictates regions of sub-linear speed for our large deviations asymptotics. Our approach is based upon various constructions of independent interest, including a decomposition of the diffusion process in terms of alternating renewal cycles and a detailed analysis of the paths during a cycle using suitable time and spatial scales. The key to the sub-linear behavior is a heavy-tailed large deviations phenomenon arising from the principle of a single big jump coupled with the result that at each regeneration cycle the upper-tail asymptotic behavior of the accumulated area of the diffusion process is proven to be semi-exponential (i.e., of heavy-tailed Weibull type).

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