Stochastic population dynamics under regime switching II
By Qi Luo, Xuerong Mao. 2007
355 citations recorded by the source corpus.
Subfields: Finance, Mathematical Physics, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/8bf7e8891ed08839262b51aa161a746bf50365e8
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Citations in the corpus
- Population dynamical behavior of Lotka-Volterra cooperative systems with random perturbations (2012, background): “Here Mao, Sabais, and Renshaw [29] revealed that the environmental noise may suppress a potential population explosion while Luo and Mao [28] showed that the stochastic model can produce many desired properties for population dynamics, for example, stochastically ultimate boundedness and the moment ”
- Sufficient and necessary conditions of stochastic permanence and extinction for stochastic logistic populations under regime switching (2011, background): “[13], [14]).”
- Global stability of a nonlinear stochastic predator-prey system with Beddington-DeAngelis functional response (2011, methodology): “The following proof is motivated by the work Luo and Mao [28].”
- Persistence and extinction in stochastic non-autonomous logistic systems (2011, neutral): “The studies [9–13] are the former type while the investigations [14–23] are the latter case.”
- Population dynamical behavior of a two-predator one-prey stochastic model with time delay (2017, methodology): “Here, enlightened by the approach used in [4, 5, 15, 17, 18, 21, 25, 27, 29, 30, 31, 32, 33, 44, 45, 52, 53, 54, 55], we consider the parameter perturbation and suppose that the environmental perturbations mainly affect the growth rates of the populations, with ri → ri + σiẆi(t), where {Wi(t)}t≥0 (i”
- Coexistence and exclusion of stochastic competitive Lotka–Volterra models (2016, background): “o environmental noise. Various types of environmental noises have been considered. General Lotka-Volterra models perturbed by white noise have been studied in [5, 9, 12, 14, 15], while the authors in [19, 20, 25, 26] go further by considering the eect of both white and colored noises to the Lotka-Vo”
- Stochastic Lotka–Volterra systems with Lévy noise (2014, background): “[2,6–8,10,12,14–17,19–21]).”
- On competitive Lotka-Volterra model in random environments (2009, result): “Compared to the results in [30–32], our model itself, rather than the random noise, suppresses population explosion.”
- Maximum Likelihood Approach to Markov Switching Models (2015, background): “, in population dynamics, see [6], or for wind forecasting, see [1].”