• Modelos de sobrevivência induzidos por fragilidade discreta com fração de cura e riscos proporcionais 

      Espírito Santo, Ana Paula Jorge do (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 21/10/2022)
      This work presents two new survival models induced by discrete frailty with unobserved heterogeneity and proportional hazards structure, for lifetime data. The first model consider the discrete frailty variable with Katz ...
    • Modelos de sobrevivência induzidos por fragilidade discreta série de potência zero-modificada 

      Molina, Katy Rocio Cruz (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 13/03/2020)
      Survival models with a frailty term are presented as an extension of Cox's proportional risk model (COX, 1972), in which a random effect, called frailty, is introduced in the risk function in a multiplicative way with the ...
    • Modelos de sobrevivência para estimação do período de latência do câncer 

      Bettim, Bárbara Beltrame (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 29/06/2017)
      Cancer is responsible for about 13% of all deaths in the world occuring mainly in people who are late diagnosed and in advanced stages. Due to its devastating characteristics and the growing prevalence of the disease, ...
    • Modelos espaciais de captura-recaptura para populações abertas 

      Pezzott, George Lucas Moraes (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 22/11/2018)
      In this thesis we propose two spatial capture-recapture models for estimation of population abundance in the open population. The proposed statistical models conform to data obtained through individual tag capture-recapture ...
    • Modelos estocásticos de transmissão para análises genéticas de características epidemiológicas 

      Lima, Milena Nascimento (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 01/08/2023)
      Epidemics can significantly affect animal production and generate large economic impacts. Furthermore, current practices for treating and controlling infectious diseases in farmed animals do not always show the desired ...
    • Modelos Lomax assimétricos: uma nova abordagem para a classificação de dados binários desbalanceados 

      Reis, Leticia Ferreira Murça (Universidade Federal de São Carlos, UFSCar, Programa de Pós-Graduação em Estatística - PPGEs, Câmpus São Carlos, 17/05/2023)
      Imbalanced data refers to a dataset where one class has significantly fewer observations than the other class. This can lead to poor performance of both machine learning algorithms and statistical models, since most of ...
    • Modelos multiestado com fragilidade 

      Costa, Renata Soares da (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 31/03/2016)
      Often intermediate events provide more detailed information about the disease process or recovery, for example, and allow greater accuracy in predicting the prognosis of patients. Such non-fatal events during the course ...
    • Modelos multivariados para dados de contagem com excesso de zeros 

      Santana, Rogério Alves (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 10/12/2019)
      In this thesis we present two new distributions for modeling multivariate counting data with overdispersion or underdispersion, zeros excess and correlation. Named the zero-inflated multivariate COM-Poisson (ZICOMP Type ...
    • Modelos não lineares assimétricos com efeitos mistos 

      Pereira, Marcos Antonio Alves (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 02/08/2019)
      This work aims to develop asymmetric nonlinear regression models with mixed-effects, which provide alternatives to the use of normal distribution and other symmetric distributions, in order to avoid the sensitivity in the ...
    • Modelos preditivos para LGD 

      Silva, João Flávio Andrade (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 04/05/2018)
      Financial institutions willing to use the advanced Internal Ratings Based (IRB) need to develop methods to estimate the LGD (Loss Given Default) risk component. Proposals for PD (Probability of default) modeling have ...
    • Modelos série de potência zero-modificado para séries temporais com dados de contagem 

      Shirozono, Aimée (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 10/05/2019)
      The goal of this work is to propose the Zero-Modified models with Power Series distribution (ZMPS) for time series with counting data. The ZMPS model have a huge portfolio of count data distributions wherein, with an ...
    • Multivariate conditional density estimation with copulas 

      Bisca, Felipe Hernandez (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 ...
    • Neural networks as an optimization tool for regression 

      Coscrato, Victor Azevedo (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 02/09/2019)
      Neural networks are a tool to solve prediction problems that have gained much prominence recently. In general, neural networks are used as a predictive method, that is, their are used to estimate a regression function. ...
    • A new class of discrete models for the analysis of zero-modified count data 

      Silva, Wesley Bertoli da (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 03/04/2020)
      In this work, a new class of discrete models for the analysis of zero-modified count data has been introduced. The proposed class is composed of hurdle versions of the Poisson-Lindley, Poisson-Shanker, and Poisson-Sujatha ...
    • New families of linear and partially linear quantile regression models under reparameterized Marshall-Olkin distributions 

      Cortés, Isaac (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 31/07/2023)
      In this dissertation, we propose families of linear and partially linear quantile regression models, where the response variable follows a reparameterized Marshall-Olkin distribution with support on the real line. This ...
    • 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 ...
    • Nonparametric pragmatic hypothesis testing 

      Lassance, Rodrigo Ferrari Lucas (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 13/06/2022)
      In statistical testing, a pragmatic hypothesis is an extension of a precise one, taking cases on the vicinity of the null as being equally worthy of appraisal. Unlike standard procedures, pragmatic hypotheses allow the ...
    • Nova classe de modelos paramétricos para análise de sistemas reparáveis 

      Lopes, Tito Lívio da Cunha (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 13/01/2023)
      The Arithimetic Reduction of Age (ARA) model class from Doyen e Gaudoin (2004) has been widely used in the analysis of repairable systems, whose repair effect is expressed by an arithmetic age reduction. However, the ...
    • 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 ...
    • Observações atípicas em alta dimensão 

      Hisatugu, Matheus Toshio (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 15/09/2022)
      Outliers and heteroskedastic noise are two common situations in Statistics. Nowadays the amount of generated data is very high and for this reason it is possible to find high dimensional data (the dimension d is just as ...