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dc.contributor.authorRomán Román, Patricia 
dc.contributor.authorSerrano-Pérez, Juan José
dc.contributor.authorTorres Ruiz, Francisco De Asís 
dc.date.accessioned2019-05-02T14:18:46Z
dc.date.available2019-05-02T14:18:46Z
dc.date.issued2018-05-21
dc.identifier.citationRomán Román, P.; Serrano-Pérez, J.J.; Torres Ruiz, F.A. Some Notes about Inference for the Lognormal Diffusion Process with Exogenous Factors. Mathematics 2018, 6, 85; doi:10.3390/math6050085.es_ES
dc.identifier.issn2227-7390
dc.identifier.urihttp://hdl.handle.net/10481/55573
dc.description.abstractDifferent versions of the lognormal diffusion process with exogenous factors have been used in recent years to model and study the behavior of phenomena following a given growth curve. In each case considered, the estimation of the model has been addressed, generally by maximum likelihood (ML), as has been the study of several characteristics associated with the type of curve considered. For this process, a unified version of the ML estimation problem is presented, including how to obtain estimation errors and asymptotic confidence intervals for parametric functions when no explicit expression is available for the estimators of the parameters of the model. The Gompertz-type diffusion process is used here to illustrate the application of the methodology.es_ES
dc.description.sponsorshipThis work was supported in part by the Ministerio de Economía, Industria y Competitividad, Spain, under Grants MTM2014-58061-P and MTM2017-85568-P.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectLognormal diffusion processes_ES
dc.subjectExogenous factorses_ES
dc.subjectGrowth curveses_ES
dc.subjectMaximum likelihood estimationes_ES
dc.subjectAsymptotic distributiones_ES
dc.titleSome Notes about Inference for the Lognormal Diffusion Process with Exogenous Factorses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.3390/math6050085


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