Large deviations for invariant measures of stochastic differential equations with jumps

Large deviations for invariant measures of stochastic differential equations with jumps
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带跳跃的随机微分方程的不变测度的大偏差

DOI:
10.1080/17442508.2018.1557184
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发表时间:
2018-12
期刊:
Stochastics-An International Journal of Probability and Stochastic Reports
影响因子:
--
通讯作者:
Xi Fubao
Xi Fubao
中科院分区:
其他
文献类型:
--
作者:
Ma Xiaocui;Xi Fubao

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给出了具有跳跃的随机微分方程不变测度的大偏差原理(LDP)。首先,我们证明给定的随机微分方程的解具有不变测度。为了保证不变测度的唯一性,证明了马尔可夫半群的强Feller性质和不可约性。此外,还建立了不变测度的LDP。LDP for的证明是基于Budhiraja等人[b]研究的LDP for。
ABSTRACT Large deviation principle (LDP) for the invariant measures of stochastic differential equations with jumps is obtained. First, we prove given as the solutions of the stochastic differential equations have invariant measures . In order to ensure the uniqueness of the invariant measures, the strong Feller property and irreducibility for the Markov semigroup are proved. Moreover, the LDP for the invariant measures is established. The proof of the LDP for is based on the LDP for , which have been studied by Budhiraja et al. [5].
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