Maximum likelihood estimation for stochastic Lotka-Volterra model with jumps

被引：2
|
作者：
Zhao, Huiyan [1 ]
Zhang, Chongqi [1 ]
Wen, Limin [2 ]
机构：
[1] Guangzhou Univ, Sch Econ & Stat, Guangzhou, Guangdong, Peoples R China
[2] Jiangxi Normal Univ, Dept Stat, Nanchang, Jiangxi, Peoples R China
来源：
ADVANCES IN DIFFERENCE EQUATIONS | 2018年
基金：
中国国家自然科学基金;
关键词：
Stochastic Lotka-Volterra model; Subordinator; Maximum likelihood estimation; Stationary distribution; STATIONARY DISTRIBUTION; POPULATION-DYNAMICS; NOISE; DIFFUSIONS; EXPANSIONS;
D O I：
10.1186/s13662-018-1605-z
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, we consider the stochastic Lotka-Volterra model with additive jump noises. We show some desired properties of the solution such as existence and uniqueness of positive strong solution, unique stationary distribution, and exponential ergodicity. After that, we investigate the maximum likelihood estimation for the drift coefficients based on continuous time observations. The likelihood function and explicit estimator are derived by using semimartingale theory. In addition, consistency and asymptotic normality of the estimator are proved. Finally, computer simulations are presented to illustrate our results.
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收藏
页数：22
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