References
- Bahar, A., and X. Mao. 2004. Stochastic delay Lotka CVolterra model. Journal of Mathematical Analysis and Applications 292 (2):364–80. doi:https://doi.org/10.1016/j.jmaa.2003.12.004.
- Bao, J., X. Mao, G. Yin, and C. Yuan. 2011. Competitive Lotka CVolterra population dynamics with jumps. Nonlinear Analysis-Theory Methods and Applications 74 (17):6601–16. doi:https://doi.org/10.1016/j.na.2011.06.043.
- Bao, J., and C. Yuan. 2012. Stochastic population dynamics driven by Lévy noise. Journal of Mathematical Analysis and Applications 391 (2):363–75. doi:https://doi.org/10.1016/j.jmaa.2012.02.043.
- Bishwal, J. P. N. 2008. Parameter estimation in stochastic differential equations. Berlin: Springer-Verlag.
- Deck, T. 2006. Asymptotic properties of Bayes estimators for Gaussian Itô processes with noisy observations. Journal of Multivariate Analysis 97 (2):563–73. doi:https://doi.org/10.1016/j.jmva.2005.04.003.
- Kan, X., H. Shu, and Y. Che. 2012. Asymptotic parameter estimation for a class of linear stochastic systems using Kalman-Bucy filtering. Mathematical Problems in Engineering 2012:1–15. 2012. doi:https://doi.org/10.15/2012/342705,.
- La Cognata, A., D. Valenti, A. A. Dubkov, et al. 2010. Dynamics of two competing species in the presence of Lévy noise sources. Physical Review E 61:11–21. doi:https://doi.org/10.1103/PhysRevE.82.011121.
- Long, H. W. 2009. Least squares estimator for discretely observed Ornstein-Uhlenbeck processes with small Lévy noises. Statistics & Probability Letters 79 (19):2076–85. doi:https://doi.org/10.1016/j.spl.2009.06.018.
- Long, H. W., Y. Shimizu, and W. Sun. 2013. Least squares estimators for discretely observed stochastic processes driven by small Lévy noises. Journal of Multivariate Analysis 116:422–39. doi:https://doi.org/10.1016/j.jmva.2013.01.012.
- Mao, X. 2011. Stationary distribution of stochastic population systems. Systems & Control Letters 60 (6):398–405. doi:https://doi.org/10.1016/j.sysconle.2011.02.013.
- Mao, X., G. Marion, and E. Renshaw. 2002. Environmental Brownian noise suppresses explosions in population dynamics. Stochastic Processes and Their Applications 97 (1):95–110. doi:https://doi.org/10.1016/S0304-4149(01)00126-0.
- Mendy, I. 2013. Parametric estimation for sub-fractional Ornstein CUhlenbeck process. Journal of Statistical Planning and Inference 143 (4):663–74. doi:https://doi.org/10.1016/j.jspi.2012.10.013.
- Protter, P. E. 2004. Stochastic integration and differential equations: Stochastic modelling and applied probability. Berlin: Springer-Verlag.
- Skouras, K. 2000. Strong consistency in nonlinear stochastic regression models. The Annals of Statistics 28 (3):871–9. doi:https://doi.org/10.1214/aos/1015952002.
- Tong, J., Z. Zhang, and J. Bao. 2013. The stationary distribution of the facultative population model with a degenerate noise. Statistics & Probability Letters 82:655–64. doi:https://doi.org/10.1016/j.spl.2012.11.003.
- Wei, C., and H. S. Shu. 2016. Maximum likelihood estimation for the drift parameter in diffusion processes. Stochastics 88 (5):699–710. doi:https://doi.org/10.1080/17442508.2015.1124879.
- Wei, C., H. S. Shu, and Y. R. Liu. 2016. Gaussian estimation for discretely observed Cox-Ingersoll-Ross model. International Journal of General Systems 45 (5):561–74. doi:https://doi.org/10.1080/03081079.2015.1106740.
- Wen, J. H., X. J. Wang, S. H. Mao, et al. 2015. Maximum likelihood estimation of McKean CVlasov stochastic differential equation and its application. Applied Mathematics and Computation 274:237–46. doi:https://doi.org/10.1016/j.amc.2015.11.019.
- Zhang, Z., X. Zhang, and J. Tong. 2017. Exponential ergodicity for population dynamics driven by α-stable processes. Statistics & Probability Letters 125:149–59. doi:https://doi.org/10.1016/j.spl.2017.02.010.
- Zhao, H., C. Zhang, and L. Wen. 2018. Maximum likelihood estimation for stochastic Lotka-Volterra model with jumps. Advances in Difference Equations 148 (1):22. doi:https://doi.org/10.1186/s13662-018-1605-z.