Publicação
Comparison of Mixture and Classification Maximum Likelihood Approaches in Poisson Regression Models
| dc.contributor.author | Faria, Susana | |
| dc.contributor.author | Soromenho, Gilda | |
| dc.date.accessioned | 2011-12-27T14:40:39Z | |
| dc.date.available | 2011-12-27T14:40:39Z | |
| dc.date.issued | 2008-08 | |
| 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.identifier.citation | Compstat 2008-Proceedings in Computational Statistics, Vol. 2 | por |
| dc.identifier.uri | http://hdl.handle.net/10451/4713 | |
| dc.language.iso | eng | por |
| dc.peerreviewed | yes | por |
| dc.subject | Simulation study | por |
| dc.subject | EM algorithm | por |
| dc.subject | Mixture Poisson Regression Models | por |
| dc.subject | Classification EM algorithm | por |
| dc.title | Comparison of Mixture and Classification Maximum Likelihood Approaches in Poisson Regression Models | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.title | Compstat 2008-Proceedings in Computational Statistics | por |
| person.familyName | Soromenho Pereira | |
| person.givenName | Gilda | |
| person.identifier.orcid | 0000-0002-4551-8642 | |
| person.identifier.scopus-author-id | 6508311775 | |
| rcaap.rights | openAccess | por |
| rcaap.type | conferenceObject | por |
| relation.isAuthorOfPublication | b2183984-e601-4ae8-a9cb-727253889566 | |
| relation.isAuthorOfPublication.latestForDiscovery | b2183984-e601-4ae8-a9cb-727253889566 |