Publicação: Solving the Levins' paradox in the logistic model to the population growth
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We introduce a new method to improve Markov maps by means of a Bayesian approach. The method starts from an initial map model, wherefrom a likelihood function is defined which is regulated by a temperature-like parameter. Then, the new constraints are added by the use of Bayes rule in the prior distribution. We applied the method to the logistic map of population growth of a single species. We show that the population size is limited for all ranges of parameters, allowing thus to overcome difficulties in interpretation of the concept of carrying capacity known as the Levins paradox. © Published under licence by IOP Publishing Ltd.
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Bayes rule, Bayesian approaches, Likelihood functions, Logistic maps, Logistic models, Markov map, Population growth, Population sizes, Prior distribution, Single species, Bayesian networks, Dynamics, Population statistics
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Inglês
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Journal of Physics: Conference Series, v. 285, n. 1, 2011.
