dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorDe Oliveira, Evaldo Araújo
dc.creatorDe Barros, Vicente Pereira
dc.creatorKraenkel, Roberto André
dc.date2014-05-27T11:25:58Z
dc.date2016-10-25T18:34:20Z
dc.date2014-05-27T11:25:58Z
dc.date2016-10-25T18:34:20Z
dc.date2011-08-30
dc.date.accessioned2017-04-06T01:51:56Z
dc.date.available2017-04-06T01:51:56Z
dc.identifierJournal of Physics: Conference Series, v. 285, n. 1, 2011.
dc.identifier1742-6588
dc.identifier1742-6596
dc.identifierhttp://hdl.handle.net/11449/72616
dc.identifierhttp://acervodigital.unesp.br/handle/11449/72616
dc.identifier10.1088/1742-6596/285/1/012023
dc.identifier2-s2.0-80052053532
dc.identifierhttp://dx.doi.org/10.1088/1742-6596/285/1/012023
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/893471
dc.descriptionWe 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.
dc.languageeng
dc.relationJournal of Physics: Conference Series
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectBayes rule
dc.subjectBayesian approaches
dc.subjectLikelihood functions
dc.subjectLogistic maps
dc.subjectLogistic models
dc.subjectMarkov map
dc.subjectPopulation growth
dc.subjectPopulation sizes
dc.subjectPrior distribution
dc.subjectSingle species
dc.subjectBayesian networks
dc.subjectDynamics
dc.subjectPopulation statistics
dc.titleSolving the Levins' paradox in the logistic model to the population growth
dc.typeOtro


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