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Atualizado em 16/11/15 20:04.

Palestra Inaugural: 

Palestrante: Prof. Ph.D. N. Balakrishnan - McMaster University Hamilton, Ontario, Canada

Título: Generalized gamma frailty model

Abstract: In this talk, I will introduce a new frailty model through generalized gamma distribution and show how it encompasses many known frailty models.  I will then discuss likelihood inference for this model using MCMC techniques, and also discuss model discrimination procedures.  Finally, I will illustrate the model and the inferential method through some real-life examples.


Palestra Inaugural :  Likelihood-based Inference for Mixed-Effects Models with Censored Response Using the Multivariate-t Distribution

Palestrante:  Prof. Ph. D. Victor Hugo Lachos Davila - UNICAMP

Abstract:  Mixed-effects models are commonly used to fit longitudinal or repeated measures data. A complication arises when the response is censored, for example, due to limits of quantification of the assay used. Although the normal distributions are commonly assumed for the random effects and the residual errors, such assumptions make inferences vulnerable in the presence of outliers. The sensitivity to outliers and the need of heavy tailed distributions for random effects and residual errors motivate us to develop a likelihood-based inference for linear and nonlinear mixed effects models with censored response (NLMEC/LMEC) based on the multivariate Student-t distribution. An ECM algorithm is developed for computing the maximum likelihood estimates for NLMEC/LMEC with the standard errors of the fixed effects and the likelihood function as a by-product. The algorithm uses the closed-form expressions at the E-step, which relies on the formulas of the mean and variance of a truncated multivariate-t distribution. The proposed algorithm is implemented in the R package tlmec. The proposed methodology is applied to analyze longitudinal HIV viral load data in the two recent AIDS studies. In addition, a simulation study is conducted to examine the performance of the proposed method and carry out the comparison with the approach by Vaida and Liu (2009).

(Joint work with Ming-Hiu Chen, Marcos Oliveira Prates and Larissa Avila Matos)


Palestra nº 2: Introdução ao mapeamento de QTL's.

Palestrante: Prof. Ph.D.Renato Rodrigues Silva – UFG


Palestra nº 3:  Estatística e Big Data na Indústria e Agronegócio

Palestrante: Doris Satie Maruyama Fontes – Presidente do CONRE-3



Mini-Palestra nº 1:   Estatística no Ministério Público de Goiás

Palestrante:  Diego Gomes Martins do Carmo

Técnico em Estatística da Superintendência de Planejamento e Gestão

do Ministério Público do Estado de Goiás


Mini-Palestra nº 2:   

Palestrante:  Mário Rodrigues Neto - Grupom Consultoria e Pesquisas.




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