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Optimization in Generalized Linear Models: a Case Study

dc.contributor.authorSilva, Eliana Costa e
dc.contributor.authorCorreia, Aldina
dc.contributor.authorLopes, Isabel Cristina
dc.date.accessioned2017-08-07T10:15:33Z
dc.date.available2017-08-07T10:15:33Z
dc.date.issued2016
dc.description.abstractThe maximum likelihood method is usually chosen to estimate the regression parameters of Generalized Linear Models (GLM) and also for hypothesis testing and goodness of fit tests. The classical method for estimating GLM parameters is the Fisher scores. In this work we propose to compute the estimates of the parameters with two alternative methods: a derivative-based optimization method, namely the BFGS method which is one of the most popular of the quasi-Newton algorithms, and the PSwarm derivative-free optimization method that combines features of a pattern search optimization method with a global Particle Swarm scheme. As a case study we use a dataset of biological parameters (phytoplankton) and chemical and environmental parameters of the water column of a Portuguese reservoir. The results show that, for this dataset, BFGS and PSwarm methods provided a better fit, than Fisher scores method, and can be good alternatives for finding the estimates for the parameters of a GLM.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1063/1.4952094pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/10195
dc.language.isoengpt_PT
dc.publisherAmerican Institute of Physicspt_PT
dc.subjectNonlinear Optimizationpt_PT
dc.subjectGeneralized Linear Modelspt_PT
dc.subjectGamma Distributionpt_PT
dc.subjectInferencept_PT
dc.subjectWater Qualitypt_PT
dc.titleOptimization in Generalized Linear Models: a Case Studypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleAIP Conference Proceedingspt_PT
person.familyNameLopes
person.givenNameIsabel Cristina
person.identifier2277025
person.identifier.ciencia-idBC14-DF88-AEBC
person.identifier.orcid0000-0002-4833-470X
person.identifier.ridL-7458-2017
person.identifier.scopus-author-id36185835200
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication70af5a18-432a-4ef9-862d-c5a79581c255
relation.isAuthorOfPublication.latestForDiscovery70af5a18-432a-4ef9-862d-c5a79581c255

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