Abstract
We consider stochastic differential equations to model the growth of a population in a randomly varying environment. These growth models are usually based on classical deterministic models, such as the logistic or the Gompertz models, taken as approximate models of the “true” (usually unknown) growth rate. We study the effect of the gap between the approximate and the “true” model on model predictions, particularly on asymptotic behavior and mean and variance of the time to extinction of the population.
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Acknowledgments
The authors are members of the CIMA (Centro de Investigação em Matemática e Aplicações), a research center of the Universidade de Évora financed by FCT (Fundação para a Ciência e Tecnologia, Portugal). Clara Carlos benefits from a PROTEC doctoral scholarship financed by IPS (Instituto Politécnico de Setúbal). Braumann gratefully acknowledges the financial support from the FCT grant PTDC/MAT/115168/2009.
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Carlos, C., Braumann, C.A. (2014). Consequences of an Incorrect Model Specification on Population Growth. In: Pacheco, A., Santos, R., Oliveira, M., Paulino, C. (eds) New Advances in Statistical Modeling and Applications. Studies in Theoretical and Applied Statistics(). Springer, Cham. https://doi.org/10.1007/978-3-319-05323-3_10
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DOI: https://doi.org/10.1007/978-3-319-05323-3_10
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