Caros Colegas, Espero que voces e suas familias estejam todos bem.Convido-os para o seminario desta semana promovido pelo Depto de Estatistica da UFMG, que sera transmitido pelo canal do Youtube video conferencia do DEST, sexta-feira, as 13:30.Nesta semana estamos recebendo o Prof. Flavio B. Gonçalves (DEST-UFMG), coordenador de nosso programa de Pos-Graduacao. Flávio tem formação em Estatistica, com Doutorado pela University of Warwick, mestrado pela UFRJ e Graduação pela UFMG. Tem se dedicado (mas nao apenas) a pesquisa nas seguintes areas: Inferência em Processos Estocásticos, Simulação Estocástica, Estatística Computacional e Teoria de Resposta ao Item e Estatística Matemática. Mais informacoes no sitio web: http://www.est.ufmg.br/~fbgoncalves/. Informacoes sobre o seminario encontram-se abaixo.Otima semana a todosRosangela****Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes<o:p></o:p>Flávio Bambirra Gonçalves (DEST-UFMG)Statistical modeling of point patterns is an important and common problem in several areas. The Poisson process is the most common process used for this purpose, in particular, its generalization that considers the intensity function to be stochastic. This is called a Cox process and different choices to model the dynamics of the intensity gives raise to a wide range of models. We present a new class of unidimensional Cox process models in which the intensity function assumes parametric functional forms that switch among them according to a continuous-time Markov chain. A novel methodology is proposed to perform exact Bayesian inference based on MCMC algorithms. The term exact refers to the fact that no discrete time approximation is used and Monte Carlo error is the only source of inaccuracy. The reliability of the algorithms depends on a variety of specifications which are carefully addressed, resulting in a computationally efficient (in terms of computing time) algorithm and enabling its use with large datasets. Simulated and real examples are presented to illustrate the efficiency and applicability of the proposed methodology. A specific model to fit epidemic curves is proposed and used to analyze data from Dengue Fever in Brazil and COVID-19 in some countries.This is joint work with Livia Dutra and Roger Silva.<o:p style=""></o:p> <span lang="PT-BR" style="line-height: 18.4px; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-attachment: initial; background-origin: initial; background-clip: initial;">DATA: 11 de setembro de 2020<span lang="PT-BR" style="line-height: 18.4px; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-attachment: initial; background-origin: initial; background-clip: initial;">HORÁRIO: 13h30<o:p></o:p><span lang="PT-BR" style="line-height: 18.4px; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-attachment: initial; background-origin: initial; background-clip: initial;">Canal Youtube: vídeo conferencia do DEST<div></div>