dc.contributor.author | Albano, Giuseppina | |
dc.contributor.author | Barrera, Antonio | |
dc.contributor.author | Giorno, Virginia | |
dc.contributor.author | Torres Ruiz, Francisco De Asís | |
dc.date.accessioned | 2025-03-11T08:32:20Z | |
dc.date.available | 2025-03-11T08:32:20Z | |
dc.date.issued | 2025-02-20 | |
dc.identifier.citation | Albano, 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/s11222-025-10562-5 | es_ES |
dc.identifier.uri | https://hdl.handle.net/10481/102980 | |
dc.description | This 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.abstract | This 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.sponsorship | MCIN/AEI/10.13039/501100011033 PID2020-1187879GB-100, CEX2020-001105-M | es_ES |
dc.description.sponsorship | “European Union – Next Generation EU” 2022XZSAFN, P2022XSF5H | es_ES |
dc.description.sponsorship | University of Granada / CBUA | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer Nature | es_ES |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Lognormal process | es_ES |
dc.subject | Gaussian Processes | es_ES |
dc.subject | Estimation | es_ES |
dc.subject | Moth-flame optimization algorithm | es_ES |
dc.title | Inference on diffusion processes related to a general growth model | es_ES |
dc.type | journal article | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/Next GenerationEU/2022XZSAFN | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/Next GenerationEU/P2022XSF5H | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.1007/s11222-025-10562-5 | |
dc.type.hasVersion | VoR | es_ES |