• 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 ...
    • Análise teórica e computacional de processos estocásticos inspirados em sistemas biológicos. 

      Pimentel, Carlos Eduardo Hirth (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 06/01/2020)
      The aim of this work is to present two methodologies based on the theoretical and computational analysis of continuous time stochastic processes inspired by biological systems, whose dynamics are influenced by the stochastic ...
    • 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 ...
    • Uma aproximação do tipo Euler-Maruyama para o processo de Cox-Ingersoll-Ross 

      Ferreira, Ricardo Felipe (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, , 26/02/2015)
      In this master's thesis we work with Cox-Ingersoll-Ross (CIR) process. This process was originally proposed by John C. Cox, Jonathan E. Ingersoll Jr. and Stephen A. Ross in 1985. Nowadays, this process is widely used in ...
    • Avaliação da proficiência em inglês acadêmico através de um teste adaptativo informatizado 

      Silva, Vanessa Rufino da (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 09/04/2015)
      This work describes the steps for converting a linear paper-and-pencil English proficiency test for academic purposes, composed with multiple choice items that are administered following the admissible probability ...
    • Avaliação do lasso e métodos alternativos em modelos de regressão logística 

      Alcântara Junior, Gilberto Pereira de (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 11/03/2021)
      Logistic regression has always been an important tool not only in the area of statistics, but also in several other areas such as economic, biological and medical. In many of these areas it is common to encounter problems ...
    • 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. ...
    • Bayesian and classical inference for the generalized gamma distribution and related models 

      Ramos, Pedro Luiz (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 22/02/2018)
      The generalized gamma (GG) distribution is an important model that has proven to be very flexible in practice for modeling data from several areas. This model has important sub-models, such as the Weibull, gamma, lognormal, ...
    • 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 ...
    • Bayesian inference for term structure models 

      Martins, Thomas Correa e Silva (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 09/06/2022)
      We explore recent advances in Bayesian methods in order to estimate the Vasicek, CIR and dynamic Nelson-Siegel (DNS) models for term structure of interest rates. The models are specified as state space time series. The ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • Cadeias estocásticas de memória ilimitada com aplicação na neurociência 

      Ferreira, Ricardo Felipe (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 21/03/2019)
      Stochastic chains with unbounded memory are a natural generalization of Markov chains, in the sense that the transition probabilities may depend on the whole past. These process, introduced independently by Onicescu and ...
    • 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 ...
    • Comparação de métodos de estimação para problemas com colinearidade e/ou alta dimensionalidade (p > n) 

      Casagrande, Marcelo Henrique (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 29/04/2016)
      This paper presents a comparative study of the predictive power of four suitable regression methods for situations in which data, arranged in the planning matrix, are very poorly multicolinearity and / or high dimensionality, ...
    • Comparing two populations using Bayesian Fourier series density estimation 

      Inacio, Marco Henrique de Almeida (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 12/04/2017)
      Given two samples from two populations, one could ask how similar the populations are, that is, how close their probability distributions are. For absolutely continuous distributions, one way to measure the proximity of ...
    • Conditional independence testing, two sample comparison and density estimation using neural networks 

      Inácio, Marco Henrique de Almeida (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 03/08/2020)
      Given the vast amount of data available nowadays and the rapid increase of computational processing power, the field of machine learning and the so called algorithmic modeling have seen a recent surge in its popularity and ...
    • Conectividade do grafo aleatório de Erdös-Rényi e uma variante com conexões locais 

      Bedia, Elizbeth Chipa (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 24/03/2016)
      We say that a graph is connected if there is a path edges between any pair of vertices. Random graph Erd os-R enyi with n vertices is obtained by connecting each pair of vertex with probability pn 2 (0; 1) independently ...