Listar Teses e dissertações por título
Mostrando ítems 139-158 de 169
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Observações atípicas em alta dimensão
(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 ... -
Penalized regression methods for compositional data
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 10/12/2018)Compositional data consist of known vectors such as compositions whose components are positive and defined in the interval (0,1) representing proportions or fractions of a "whole", where the sum of these components must ... -
Percolação Acessível
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 17/02/2020)We consider the accessibility percolation model on the n-ary tree height the _nite h. The model is de_ned by associating a continuous random variable X_v for each vertex v in the tree. The main issue to consider and ... -
Poincaré recurrence times in stochastic mixing processes
(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 ... -
Um procedimento para seleção de variáveis em modelos lineares generalizados duplos
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 01/04/2019)The double generalized linear models (DGLM), unlike the generalized linear model (GLM), allow the fit of the dispersion parameter of the response variable as a function of predictor variables, improving the way of modeling ... -
Processo de Bernoulli correlacionado
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 28/06/2019)The independent Bernoulli process, which is a sequence of independent Bernoulli random variables, is already widely known in the statistical literature. This masters thesis works with a generalization of this process: the ... -
Programação linear aplicada a estatística
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 27/11/2017)Determine probabilities for events where we have few information or intervals for probabilities is not so simple. For this we will develop concepts of linear programming, which allows us to solve, in a certain way, the ... -
Propagação de rumor em uma população cética em N
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 30/03/2023)We consider two models for information propagation in N. In both models, the individuals (one per site of N) have random, independent, and equally distributed radius. At the beginning only the individual at 0 has the ... -
Quantificação em problemas com mudança de domínio
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 17/05/2018)Several machine learning applications use classifiers as a way of quantifying the prevalence of positive class labels in a target dataset, a task named quantification. For instance, a naive way of determining what proportion ... -
Redes Bayesianas para classificação com aprendizado via scoring and restrict: método, aplicação e comparação com métodos tradicionais
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, 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 ... -
Redes neurais para grafos e suas aplicações aos sistemas complexos
(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 ... -
Regressão binária nas abordagens clássica e bayesiana
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 16/12/2016)The objective of this work is to study the binary regression model under the frequentist and Bayesian approaches using the probit, logit, log-log complement, Box-Cox transformation and skewprobit as link functions. In the ... -
Regressão binária usando ligações potência e reversa de potência
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 07/04/2017)The aim of this dissertation is to study a family of asymmetric link functions for binary regression models under Bayesian approach. Specifically, we present the estimation of parameters of power and reversal power binary ... -
Regularização social em sistemas de recomendação com filtragem colaborativa
(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
(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
(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
(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 ... -
Rumour spreading in dynamic random graphs
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 19/02/2024)We study rumour spreading in dynamic random graphs. Starting with a single informed vertex, the information flows until it reaches all the vertices of the graph (completion), according to the following process. At each ... -
Scalable and interpretable kernel methods based on random Fourier features
(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
(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 ...