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dc.contributor.authorDi Crescenzo, Antonio
dc.contributor.authorParaggio, Paola
dc.contributor.authorTorres-Ruiz, Francisco 
dc.date.accessioned2024-09-02T11:28:41Z
dc.date.available2024-09-02T11:28:41Z
dc.date.issued2024-08-03
dc.identifier.citationDi Crescenzo, A. & Paraggio, P. & Torres Ruíz, F. 139 (2024) 108258. [https://doi.org/10.1016/j.cnsns.2024.108258]es_ES
dc.identifier.urihttps://hdl.handle.net/10481/93787
dc.description.abstractWe analyze a modification of the Richards growth model by introducing a time-dependent perturbation in the growth rate. This modification becomes effective at a special switching time, which represents the first-crossing-time of the Richards growth curve through a given constant boundary. The relevant features of the modified growth model are studied and compared with those of the original one. A sensitivity analysis on the switching time is also performed. Then, we define two different stochastic processes, i.e. a non-homogeneous linear birth–death process and a lognormal diffusion process, such that their means identify to the growth curve under investigation. For the diffusion process, we address the problem of parameters estimation through the maximum likelihood method. The estimates are obtained via metaheuristic algorithms (namely, Simulated Annealing and Ant Lion Optimizer). A simulation study to validate the estimation procedure is also presented, together with a real application to oil production in France. Special attention is devoted to the approximation of switching time density, viewed as the first-passage-time density for the lognormal process.es_ES
dc.description.sponsorship‘‘Ministerio de Ciencia e Innovación, Spain, under Grant PID2020-1187879GB-100, and ‘‘María de Maeztu’’es_ES
dc.description.sponsorshipExcellence Unit IMAG, reference CEX2020-001105-M, funded by MCIN/AEI/10.13039/501100011033/es_ES
dc.description.sponsorship‘European Union – Next Generation EU’ through MUR-PRIN 2022es_ES
dc.description.sponsorshipproject 2022XZSAFN ‘‘Anomalous Phenomena on Regular and Irregular Domains: Approximating Complexity for the Applied Sciences’’es_ES
dc.description.sponsorshipMUR-PRIN 2022 PNRR, project P2022XSF5H ‘‘Stochastic Models in Biomathematics and Applications’’es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectRichards growth modeles_ES
dc.subjectNon-homogeneous birth–death processes_ES
dc.subjectLognormal diffusion processes_ES
dc.titleA Bertalanffy–Richards growth model perturbed by a time-dependent pattern, statistical analysis and applications✩es_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.cnsns.2024.108258
dc.type.hasVersionVoRes_ES


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