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https://hdl.handle.net/1822/26551
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Campo DC | Valor | Idioma |
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dc.contributor.author | Faria, Susana | - |
dc.contributor.author | Soromenho, Gilda | - |
dc.date.accessioned | 2013-12-02T14:51:07Z | - |
dc.date.available | 2013-12-02T14:51:07Z | - |
dc.date.issued | 2008-08 | - |
dc.identifier.uri | https://hdl.handle.net/1822/26551 | - |
dc.description.abstract | In this work, we propose to compare two algorithms to compute maximum likelihood estimators of the parameters of a mixture Poisson regression models. To estimate these parameters, we may use the EM algorithm in a mixture approach or the CEM algorithm in a classification approach. The comparison of the two procedures was done through a simulation study of the performance of these approaches on simulated data sets in a target number of iterations. Simulation results show that the CEM algorithm is a good alternative to the EM algorithm for fitting Poisson mixture regression models, having the advantage of converging more quickly. | por |
dc.description.sponsorship | Fundação para a Ciência e a Tecnologia (FCT) | por |
dc.language.iso | eng | por |
dc.publisher | Springer | por |
dc.rights | restrictedAccess | por |
dc.subject | Maximum likelihood estimation | por |
dc.subject | EM algorithm | por |
dc.subject | Classification EM algorithm | por |
dc.subject | Mixture poisson regression models | por |
dc.subject | Simulation study | por |
dc.title | Comparison of mixture and classification maximum likelihood approaches in poisson regression models | por |
dc.type | conferencePaper | - |
dc.peerreviewed | yes | por |
sdum.publicationstatus | published | por |
oaire.citationConferenceDate | 24-29 Agosto 2008 | por |
sdum.event.type | congress | por |
oaire.citationStartPage | 69 | por |
oaire.citationEndPage | 77 | por |
oaire.citationConferencePlace | Porto, Portugal | por |
oaire.citationTitle | International Conference on Computational Statistics (COMPSTAT) | por |
sdum.conferencePublication | International Conference on Computational Statistics (COMPSTAT) | por |
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artigo15-01.pdf Acesso restrito! | Documento Principal | 207 kB | Adobe PDF | Ver/Abrir |