• Detecting influential observations in spatial models using Bregman divergence 

      Danilevicz, Ian Meneghel (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 26/02/2018)
      How to evaluate if a spatial model is well ajusted to a problem? How to know if it is the best model between the class of conditional autoregressive (CAR) and simultaneous autoregressive (SAR) models, including homoscedasticity ...
    • Métodos de Monte Carlo Hamiltoniano aplicados em modelos GARCH 

      Xavier, Cleber Martins (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 26/04/2019)
      One of the most important informations in financial market is variability of an asset. Several models have been proposed in literature with a view of to evaluate this phenomenon. Among them we have the GARCH models. This ...
    • Método Zero-Variance para Monte Carlo Hamiltoniano aplicado a modelos GARCH univariados e multivariados 

      Paixão, Rafael Soares (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 13/05/2021)
      This PhD work develops, compares and applies Monte Carlo Markov Chains (MCMC) methods for parameter estimation in univariate and multivariate GJR-GARCH models. Specifically, the following problems are addressed: (i) ...