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  • Redes neurais para grafos e suas aplicações aos sistemas complexos 

    Carvalho, Guilherme Michel Lima de (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 08/04/2022)
    Complex systems are composed of several components that interact with each other. A natural approach for these types of systems is to use mathematical graph abstraction. In different contexts in the real world, it is ...
  • Testes bayesianos em ensaios clínicos 

    Silva, Josimara Tatiane da (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 22/02/2022)
    In this thesis, we propose two new Bayesian approaches for equivalence hypotheses testing for proportions and prove that these Bayesian hypotheses tests are equivalent. These Bayesian methodologies applied to equivalence ...
  • Poincaré recurrence times in stochastic mixing processes 

    Amorim, Vitor Gustavo de (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 17/02/2022)
    In the context of the discrete-time stochastic processes, this thesis presents new results on Poincaré recurrence theory. After a complete review of recent results, we present a new theorem on the exponential approximations ...
  • 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 ...
  • Lambert-F univariate distributions for asymmetrical data 

    Iriarte Salinas, Yuri Antonio (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 16/12/2021)
    In this dissertation, we propose new univariate continuous distributions for modeling asymmetrical data. Initially, starting from a non-linear parametric transformation of an uniform random variable, we propose a new ...
  • A robust lasso regression for linear mixed-effects models with diagnostic analysis 

    Garcia, Rafael Rocha de Oliveira (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 22/10/2021)
    Variable selection has been a topic of great interest for statisticians and researchers alike. The choice of the best subset of predictors may be carried out with the objective of improving prediction or for easier ...
  • Multivariate conditional density estimation with copulas 

    Bisca, Felipe (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 29/09/2021)
    Most machine learning regression models only yield single point estimations for the label of a new observation. However, when dealing with multi-modal or asymmetric distributions, a single point estimate is not enough to ...
  • Método bagging para aprimoramento de previsões de séries temporais 

    Camargo, Juliana Shibaki (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 22/10/2021)
    Different methodologies are proposed and explored aiming to reduce time series forecasting error. A promising approach consists in combining different forecasts from different models in order to get a better accuracy, ...
  • Resultados para o modelo de rumor de Maki-Thompson em árvores 

    Speroto, Adalto (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 20/04/2021)
    In this work, we study the Maki-Thompson rumor model on infinite homogeneous trees which is formulated as a continuous-times Markov chain. This model can be defined as a system of interacting particles representing the ...
  • Bandas de predição usando densidade condicional estimada e um modelo LDA com covariáveis 

    Shimizu, Gilson Yuuji (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 15/10/2021)
    Machine learning methods are divided into two main groups: supervised and unsupervised methods. In the first part of this work, we develop a method for creating prediction bands that can be applied to supervised problems. ...
  • Análises Bayesiana para o modelo de regressão Birnbaum-Saunders com zeros ajustados 

    Marcelino, Jadson Luan dos Santos (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 11/08/2021)
    Modeling based on the Birnbaum-Saunders distribution has received considerable attention in recent years. In this work we consider the reparametrized Birnbaum-Saunders distribution with zero-adjusted (ZARBS) (SANTOS-NETO ...
  • Distribuições discretas para duas observações inflacionadas 

    Hebling, Luisa (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 30/07/2021)
    Count data is often found in many real applications and some observations may occur in the data set in an excessive amount. In many real problems it is quite common for the data set to contain excesses of zero and one ...
  • Full Bayesian Significance Test para dados de sobrevivência bivariados: seleção de modelos encaixados da cópula PVF 

    Cantoni, Murilo (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 28/06/2021)
    The investigation and modeling of the existing dependence in a set of random variables is a widely discussed topic in statistics. In this context, the use of copulas becomes interesting because it is a flexible approach ...
  • Frailty model for multiple repairable systems hierarchically represented in serial/parallel structures under assumption of ARAm imperfect repairs 

    Gonzatto Junior, Oilson Alberto (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 27/04/2021)
    The main objective of this thesis is to extend the methodology used to treat failure time data. In particular, we wish to propose an appropriate modeling to a context of hierarchically represented repairable systems, subject ...
  • 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) ...
  • Redes Bayesianas para classificação com aprendizado via scoring and restrict: método, aplicação e comparação com métodos tradicionais 

    Ozelame, Camila Sgarioni (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Ciências Fisiológicas - PIPGCF, Câmpus São Carlos, 05/04/2021)
    This work is an investigation towards the behavior of discrete Bayesian Networks (BN) which aims to solve classification problems. This methodology is based on graphs and probability theories, and it is defined to be ...
  • Um novo modelo de sobrevivência Bell-Inversa Gaussiana com fração de cura 

    Carregari, Renata Cristina (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 26/03/2021)
    In this work we propose a new survival model called the Bell-Inverse Gaussian cure rate. We consider different activation schemes in which the number of factors $M$ has the Bell distribution and the time of occurrence ...
  • Análise de textos por meio de processos estocásticos na representação word2vec 

    Massoni, Gabriela (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 03/03/2021)
    Within the field of Natural Language Processing (NLP), the word2vec model has been extensively explored in the field of vector representation of words. It is a neural network that is based on the hypothesis that similar ...
  • Distribuições combinadas 

    Caldas, Tainá Santana (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 21/04/2021)
    It is proposed a possible new line of research in which distributions are combined. Combined distributions are an alternative for adjusting continuous data that present different probabilistic behaviors. A combined ...
  • Regularização social em sistemas de recomendação com filtragem colaborativa 

    Zabanova, Tatyana (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Ciências Fisiológicas - PIPGCF, Câmpus São Carlos, 14/05/2019)
    Models based on matrix factorization are among the most successful implementations of Recommender Systems. In this project, we study the possibilities of incorporating the information from social networks to improve the ...

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