Maximum likelihood estimation for stochastic Lotka–Volterra model with jumps

Abstract 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...

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Bibliographic Details
Main Authors: Huiyan Zhao, Chongqi Zhang, Limin Wen
Format: Article
Language:English
Published: SpringerOpen 2018-04-01
Series:Advances in Difference Equations
Subjects:
Online Access:http://link.springer.com/article/10.1186/s13662-018-1605-z
Description
Summary:Abstract 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.
ISSN:1687-1847