Exponential ergodicity for stochastic equations of nonneg- ative processes with jumps

被引:1
作者
Friesen, Martin [1 ]
Jin, Peng [2 ,3 ]
Kremer, Jonas [4 ]
Ruediger, Barbara [4 ]
机构
[1] Dublin City Univ, Sch Math Sci, Dublin, Ireland
[2] BNU HKBU United Int Coll, Guangdong Prov Key Lab, IRADS, Zhuhai 519087, Peoples R China
[3] Shantou Univ, Dept Math, Shantou 515063, Guangdong, Peoples R China
[4] Univ Wuppertal, Sch Math & Nat Sci, D-42119 Wuppertal, Germany
来源
ALEA-LATIN AMERICAN JOURNAL OF PROBABILITY AND MATHEMATICAL STATISTICS | 2023年 / 20卷
关键词
Branching process; random environment; invariant distribution; ergodicity; coupling; Wasserstein distance; STATE BRANCHING-PROCESSES; DIFFERENTIAL-EQUATIONS; SUBGEOMETRIC RATES; DISTRIBUTIONS; CONVERGENCE; BEHAVIOR; DRIVEN; SDES;
D O I
10.30757/ALEA.v20-22
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We study the long-time behavior for continuous-time Markov processes on the state space R>0 :_ [0, infinity), which arise as unique strong solutions to stochastic equations with jumps. We establish, under a global dissipativity condition combined with a comparison principle, exponential ergodicity in various Wasserstein distances on R>0. Our main emphasis lies on the derivation of these estimates under minimal moment conditions to be imposed on the associated Levy measures of the noises. We apply our method to continuous-state branching processes with immigration (shorted as CBI processes), to nonlinear CBI processes, and finally to CBI processes in Levy random environments.
引用
收藏
页码:593 / 627
页数:35
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