Browsing Teses e dissertações by Subject "Variable selection"

Now showing items 1-4 of 4

    • Bayesian variable selection using data driven reversible jump: an application to schizophrenia data 

      Montcho, Djidenou Hans Amos (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 17/12/2021)
      Symptom based diagnosis are known to be limited specially concerning complex disorders such as schizophrenia. Modern attempts in providing predictive risk for such disease, to assist existing diagnosis tools, integrate ...

    • Bayesian variable selection for logistic mixture models with Pólya-Gamma data augmentation 

      Bogoni, Mariella Ananias (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 15/02/2022)
      In this work, Bayesian methods for estimating and selecting variables in a mixture of logistic regressions model are presented. In order to simplify its Bayesian estimation, we extend the data augmentation approach ...

    • Penalized regression methods for compositional data 

      Shimizu, Taciana Kisaki Oliveira (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 10/12/2018)
      Compositional data consist of known vectors such as compositions whose components are positive and defined in the interval (0,1) representing proportions or fractions of a "whole", where the sum of these components must ...

    • Um procedimento para seleção de variáveis em modelos lineares generalizados duplos 

      Cavalaro, Lucas Leite (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 01/04/2019)
      The double generalized linear models (DGLM), unlike the generalized linear model (GLM), allow the fit of the dispersion parameter of the response variable as a function of predictor variables, improving the way of modeling ...