Brasil
| Tesis
Métodos de estimação em modelos de efeitos mistos não lineares de caudas pesadas
dc.contributor | Novelli, Cibele Maria Russo | |
dc.contributor | http://lattes.cnpq.br/1011098065426388 | |
dc.contributor | http://lattes.cnpq.br/7522100387675610 | |
dc.creator | Gomes, José Clelto Barros | |
dc.date.accessioned | 2020-03-11T12:28:10Z | |
dc.date.accessioned | 2022-10-10T21:30:32Z | |
dc.date.available | 2020-03-11T12:28:10Z | |
dc.date.available | 2022-10-10T21:30:32Z | |
dc.date.created | 2020-03-11T12:28:10Z | |
dc.date.issued | 2019-12-05 | |
dc.identifier | GOMES, José Clelto Barros. Métodos de estimação em modelos de efeitos mistos não lineares de caudas pesadas. 2019. Tese (Doutorado em Estatística) – Universidade Federal de São Carlos, São Carlos, 2019. Disponível em: https://repositorio.ufscar.br/handle/ufscar/12312. | |
dc.identifier | https://repositorio.ufscar.br/handle/ufscar/12312 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/4042804 | |
dc.description.abstract | Parameter estimation in nonlinear mixed-effects models is often challenging. In this thesis, a comparison of estimation methods for these models is proposed under a frequentist approach. In the first study, a comparison of maximum likelihood estimates under an exact method via Monte Carlo expectation-maximization (MCEM) and an approximate method based on a Taylor expansion, frequently used in the literature, is provided. In a second study, a restricted maximum likelihood estimation method is proposed, aiming to decrease the bias for the variance components estimates, based on the integration of the likelihood function on the fixed-effects, also in an exact likelihood context. These estimates are compared to the maximum likelihood ones. For the latter comparison, stochastic approximation of expectation-maximization (SAEM) algorithms are considered. The random effects and errors are assumed to follow multivariate symmetric distributions, namely the scale mixture of normal distributions, which include the normal, t and slash distributions. Finally, a general nonlinear mixed-effects model is proposed, where no linear relation is assumed in the random effects structure. In all the proposals, real data sets and simulation studies are used to illustrate the estimates’ properties. | |
dc.language | eng | |
dc.publisher | Universidade Federal de São Carlos | |
dc.publisher | UFSCar | |
dc.publisher | Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs | |
dc.publisher | Câmpus São Carlos | |
dc.rights | http://creativecommons.org/licenses/by-nc-nd/3.0/br/ | |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Brazil | |
dc.subject | Nonlinear models | |
dc.subject | Mixed-effects models | |
dc.subject | Correlated data | |
dc.subject | Estimation methods | |
dc.subject | Maximum likelihood | |
dc.subject | Restricted maximum likelihood | |
dc.subject | Modelos não-lineares | |
dc.subject | Modelos mistos | |
dc.subject | Dados correlacionados | |
dc.subject | Métodos de estimação | |
dc.subject | Máxima verossimilhança | |
dc.subject | Máxima verossimilhança restrita | |
dc.title | Métodos de estimação em modelos de efeitos mistos não lineares de caudas pesadas | |
dc.type | Tesis |