论文标题
不变措施的较大偏差限制
Large deviation limits of invariant measures
论文作者
论文摘要
本文涉及将大偏差原理（LDP）与相关样品路径LDP的不变度度量相关的一般主题。结果表明，如果样品路径偏差函数具有某些结构，并且不变措施成倍紧密，则样本路径LDP暗示了不变度度量的LDP，则没有其他的随机过程的其他特性为物质。作为应用程序，我们获得了用于跳跃扩散的固定分布的LDP。大偏差收敛和愿意概率的方法起着不可或缺的作用。
This paper is concerned with the general theme of relating the Large Deviation Principle (LDP) for the invariant measures of stochastic processes to the associated sample path LDP. It is shown that if the sample path deviation function possesses certain structure and the invariant measures are exponentially tight, then the LDP for the invariant measures is implied by the sample path LDP, no other properties of the stochastic processes in question being material. As an application, we obtain an LDP for the stationary distributions of jump diffusions. Methods of large deviation convergence and idempotent probability play an integral part.
