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dc.contributor.authorAlbano, Giuseppina
dc.contributor.authorBarrera, Antonio
dc.contributor.authorGiorno, Virginia
dc.contributor.authorTorres Ruiz, Francisco De Asís 
dc.date.accessioned2025-03-11T08:32:20Z
dc.date.available2025-03-11T08:32:20Z
dc.date.issued2025-02-20
dc.identifier.citationAlbano, G., Barrera, A., Giorno, V. et al. Inference on diffusion processes related to a general growth model. Stat Comput 35, 52 (2025). https://doi.org/10.1007/s11222-025-10562-5es_ES
dc.identifier.urihttps://hdl.handle.net/10481/102980
dc.descriptionThis research is partially supported by PID2020-1187879GB-100 and CEX2020-001105-M grants, funded by MCIN/AEI/10.13039/501100011033 (Spain). The authors G. Albano and V. Giorno acknowledge support received from the “ European Union – Next Generation EU” through MUR-PRIN 2022, project 2022XZSAFN “Anomalous Phenomena on Regular and Irregular Domains: Approximating Complexity for the Applied Sciences,” and MUR-PRIN 2022 PNRR, project P2022XSF5H “ Stochastic Models in Biomathematics and Applications.”. They are members of the GNCS-INdAM. Funding for open access charge: University of Granada / CBUA.es_ES
dc.description.abstractThis paper considers two stochastic diffusion processes associated with a general growth curve that includes a wide family of growth phenomena. The resulting processes are lognormal and Gaussian, and for them inference is addressed by means of the maximum likelihood method. The complexity of the resulting system of equations requires the use of metaheuristic techniques. The limitation of the parameter space, typically required by all metaheuristic techniques, is also provided by means of a suitable strategy. Several simulation studies are performed to evaluate to goodness of the proposed methodology, and an application to real data is described.es_ES
dc.description.sponsorshipMCIN/AEI/10.13039/501100011033 PID2020-1187879GB-100, CEX2020-001105-Mes_ES
dc.description.sponsorship“European Union – Next Generation EU” 2022XZSAFN, P2022XSF5Hes_ES
dc.description.sponsorshipUniversity of Granada / CBUAes_ES
dc.language.isoenges_ES
dc.publisherSpringer Naturees_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectLognormal processes_ES
dc.subjectGaussian Processeses_ES
dc.subjectEstimationes_ES
dc.subjectMoth-flame optimization algorithmes_ES
dc.titleInference on diffusion processes related to a general growth modeles_ES
dc.typejournal articlees_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/Next GenerationEU/2022XZSAFNes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/Next GenerationEU/P2022XSF5Hes_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1007/s11222-025-10562-5
dc.type.hasVersionVoRes_ES


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