Browsing Teses e dissertações by CNPq Subject "CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA::ESTATISTICA::INFERENCIA NAO-PARAMETRICA"

Now showing items 1-11 of 11

    • Classe de modelos de fragilidade com efeito do acúmulo de reparos em múltiplos sistemas reparáveis 

      D'Andrea, Amanda Morales Eudes (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 13/12/2019)
      In repairable systems, a fundamental aspect to be considered is predict the reliability of the systems being studied. However, the standard methods used to analyze reparable system data ignore the cumulative effect of ...

    • Modelo de mistura de regressão: uma abordagem bayesiana 

      Cotrim, Luiz Gabriel Fernandes (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 14/04/2020)
      In the current dissertation, we study the mixture regression models and present two Bayesian methodologies for their estimation. The first one considers the number of components is known and we propose the use of two ...

    • Estimação de funções do redshift de galáxias com base em dados fotométricos 

      Ferreira, Gretta Rossi (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 18/09/2017)
      In a substantial amount of astronomy problems, we are interested in estimating values assumed of some unknown quantity z ∈ R, for many function g, based on covariates x ∈ R^d. This is made using a sample (X1,Z1), ... ...

    • Statistical inference for non-homogeneous Poisson process with competing risks: a repairable systems approach under power-law process 

      Almeida, Marco Pollo (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 30/08/2019)
      In this thesis, the main objective is to study certain aspects of modeling failure time data of repairable systems under a competing risks framework. We consider two different models and propose more efficient Bayesian ...

    • Bayesian spatial process models for activation patterns in transcranial magnetic stimulation mapping 

      Egbon, Osafu Augustine (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 07/07/2023)
      In recent years, Spatial statistical models have been gaining rapid attention for solving problems in biological systems due to the improvement in spatial data collection. It has proven extremely important in unveiling ...

    • Testes de superioridade para modelos de chances proporcionais com e sem fração de cura 

      Teixeira, Juliana Cecília da Silva (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 24/10/2017)
      Studies that prove the superiority of a drug in relation to others already existing in the market are of great interest in clinical practice. Based on them the Brazilian National Agency of Sanitary Surveillance (ANVISA) ...

    • A bayesian nonparametric approach for the two-sample problem 

      Console, Rafael de Carvalho Ceregatti de (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 19/11/2018)
      In this work, we discuss the so-called two-sample problem (PEARSON; NEYMAN, 1930) assuming a nonparametric Bayesian approach. Considering X 1 ,...,X n and Y 1 ,...,Y m two inde- pendent i.i.d samples generated from P 1 ...

    • A nonparametric bayesian approach for modeling and comparison of functional data 

      Moreira, Diogo Barboza (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 02/09/2022)
      The current advances of technology provides, among other things, several ways of collecting data, which enlarges the possibility of studying new phenomena. Researches focused on studying the functional relation between ...

    • Scalable and interpretable kernel methods based on random Fourier features 

      Otto, Mateus Piovezan (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 29/03/2023)
      Kernel methods are a class of statistical machine learning models based on positive semidefinite kernels, which serve as a measure of similarity between data features. Examples of kernel methods include kernel ridge ...

    • Bayesian estimation of dynamic mixture models by wavelets 

      Motta, Flávia Castro (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 20/04/2023)
      Gaussian mixture models are used successfully in various statistical learning applications. The good results provided by these models encourage several generalizations of them. Among possible adaptations, one can assume a ...

    • Small and time-efficient distribution-free predictive regions 

      Reis, Victor Candido (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 02/05/2023)
      Predicting a target variable (response) is often the main objective of many studies and investigations. In such scenarios, there are usually other variables, known as covariates, that are more readily available and can ...