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Bayesian Estimation for Performance Measures of Two Diagnostic Tests in the Presence of Verification Bias
(TAYLOR & FRANCIS INCNEW YORK, 2010)
Sensitivity and specificity are measures that allow us to evaluate the performance of a diagnostic test. In practice, it is common to have situations where a proportion of selected individuals cannot have the real state ...
Modelos exponenciais para grafos aleatórios valorados
(Universidade Federal de Minas GeraisUFMG, 2018-05-14)
Exponential Random Graph Models (ERGM) are statistical models for network structure, which allows us to make inferences about the generating process of such structures. They are based on three main statistics: edges, k-stars ...
Modelagem espaco-temporal de processos pontuais: aplicação em circuitos de televisão para controle de crimes
(Universidade Federal de Minas GeraisUFMG, 2016-02-25)
The increase in population over the centuries has led to signicant impacts on various factors belonging to the everyday life of society, criminality is the principal among them. Therefore, for the authorities, to monitor ...
Bayesian analysis of extreme events with threshold estimation
(Fundação Getulio Vargas. Escola de Pós-graduação em Economia, 2004-08-20)
The aim of this paper is to analyze extremal events using Generalized Pareto Distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines this quantity and proceeds ...
Comparação de estratégias de geração de propostas no algoritmo Metropolis-Hastings para um modelo Poisson log-linear
(Universidade Federal de Minas GeraisUFMG, 2016-02-26)
The Markov Chain Monte Carlo methods (MCMC) are a class of simulation algorithms widely used in Bayesian inference to indirectly draw samples from the posterior distribution, which is known up to a constant of proportionality. ...