Navegando Teses e dissertações por título
Itens para a visualização no momento 126-145 of 169
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Modelos não lineares assimétricos com efeitos mistos
(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
(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
(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 ... -
Modelos Skellam generalizados
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 24/06/2024)In applied statistics, counting data are often observed in different areas of study. Due to the great diversity of problems that result in these types of data, it is necessary to propose new models. In this work, we propose ... -
Multivariate conditional density estimation with copulas
(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
(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
(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
(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
(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
(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
(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 ... -
Novas modelagens de risco aditivo com fragilidade para análise de dados de sobrevivência
(Universidade Federal de São Carlos, UFSCar, Programa Interinstitucional de Pós-Graduação em Estatística - PIPGEs, Câmpus São Carlos, 01/03/2024)Survival analysis emerges as a valuable statistical area for examining the time until the occurrence of events of interest. Several models were designed and applied in different areas such as: Medicine, Engineering, ... -
Um novo modelo de sobrevivência Bell-Inversa Gaussiana com fração de cura
(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
(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 ...