Browsing Teses e dissertações by Title

Now showing items 142-158 of 158

    • Regularização social em sistemas de recomendação com filtragem colaborativa 

      Zabanova, Tatyana (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, 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 ...

    • Reliability analysis of repairable systems considering unobserved heterogeneity and competing risks 

      Brito, Éder Silva de (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 09/10/2023)
      In repairable systems, the failure process defined by the failure intensity function can be impacted by three crucial characteristics: the type of repair performed after the failures occur, the underlying cause of the ...

    • 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 ...

    • 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 ...

    • 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 ...

    • Seleção de covariância para o modelo grafo gaussiano via reversible jump 

      Santos, Eriton Barros dos (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 24/02/2023)
      The purpose of the Graphical Gaussian model is to find the covariance structure that represents the relationship between random variables, whose joint distribution is a multivariate normal. This is a tool used to modeling ...

    • Seleção de modelos multiníveis para dados de avaliação educacional 

      Coelho, Fabiano Rodrigues (Universidade Federal de São Carlos, UFSCar, Programa de Pós-graduação em Estatística - Interinstitucional (PIPGEs), Câmpus São Carlos, 11/08/2017)
      When a dataset contains a hierarchical data structure, a possible approach is the multilevel regression modelling, which is justified by the significative amout of the data variability that can be explained by macro level ...

    • 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 ...

    • Some extensions in measurement error models 

      Cáceres Tomaya, Lorena Yanet (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 14/12/2018)
      In this dissertation, we approach three different contributions in measurement error model (MEM). Initially, we carry out maximum penalized likelihood inference in MEM’s under the normality assumption. The methodology ...

    • 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 ...

    • Tempo de espera para a ocorrência de palavras em ensaios de Markov 

      Florencio, Mariele Parteli (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 06/04/2016)
      Consider a sequence of independent coin flips where we denote the result of any landing for H, if coming up head, or T, otherwise. Create patterns with H's and T's, for example, HHHHH or HTHTH. How many times do we have ...

    • Teoremas limite para variáveis aleatórias de Bernoulli dependentes 

      Rezende, Bruna Luiza de Faria (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 22/03/2023)
      In this work, we consider a sequence of correlated Bernoulli variables whose probability of success for the current trial depends conditionally on previous trials. This conditional probability is given as a linear function ...

    • 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 ...

    • 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) ...

    • Técnicas de classificação aplicadas a credit scoring: revisão sistemática e comparação 

      Frazzato Viana, Renato (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 18/12/2015)
      Nowadays the increasing amount of bank transactions and the increasing of data storage created a demand for risk evaluation associated with personal loans. It is very important for a company has a very good tools in credit ...

    • Using VAE for incomplete educational data 

      Escobar Montecino, Claudia Evelyn (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 13/03/0023)
      In Psychometrics, especially in educational assessments, incomplete databases are common. An individual may leave items unanswered in an assessment due to lack of time, forgetting the content involved, nervousness, or ...

    • Vector representation of texts applied to prediction models 

      Stern, Deborah Bassi (Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 09/03/2020)
      Natural Language Processing has gone through substantial changes over time. It was only recently that statistical approaches started receiving attention. The Word2Vec model is one of these. It is a shallow neural network ...