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Maximum likelihood estimation for stochastic Lotka – Volterra model with jumps
| Content Provider | Semantic Scholar |
|---|---|
| Author | Zhao, Huiyan Zhang, Cheng Wen, Limin |
| Copyright Year | 2018 |
| 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://advancesindifferenceequations.springeropen.com/track/pdf/10.1186/s13662-018-1605-z |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Coefficient Computer simulation Ergodicity Maximum Likelihood Estimation Normality Unit Phenylephrine Hydrochloride 10 MG Oral Tablet Stationary process Utility functions on indivisible goods exponential |
| Content Type | Text |
| Resource Type | Article |
