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Influência local com procura "forward' em modelos de regressão linear
(Universidade Federal de São Carlos, 2015-02-25)
The identification of influential and/or atypical observations in a data set is known as a part of the diagnostic analysis. One of the purposes of the diagnostic analysis is to verify the robustness of a statistical model, ...
O corte do FBST em modelos de alta dimensionalidade
(Universidade Federal de São Carlos, 2018-12-03)
The problem of controlling the significance level of the FBST (Full Bayesian Significant Test) test
is studied in the context of Bayesian models for density, thus, a Bayesian method is shown that
works with density ...
O Modelo de Regressão Potência-Normal Logística, Cauchy, Normal e Gumbel para resposta no intervalo unitário
(Universidade Federal de São Carlos, 2020-07-17)
In this research a new statistical model is introduced to model data restricted in the continuous interval (0,1) . The new model is the composition of the power-normal distribution and the quantile of another family of ...
Métodos de estimação em modelos de efeitos mistos não lineares de caudas pesadas
(Universidade Federal de São Carlos, 2019-12-05)
Parameter estimation in nonlinear mixed-effects models is often challenging. In this thesis,
a comparison of estimation methods for these models is proposed under a frequentist
approach. In the first study, a comparison ...
Uma aproximação do tipo Euler-Maruyama para o processo de Cox-Ingersoll-Ross
(Universidade Federal de São Carlos, 2015-02-26)
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 ...
Análise teórica e computacional de processos estocásticos inspirados em sistemas biológicos.
(Universidade Federal de São Carlos, 2020-01-06)
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 ...
Bandas de predição usando densidade condicional estimada e um modelo LDA com covariáveis
(Universidade Federal de São Carlos, 2021-10-15)
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. ...
Modelo de regressão chances de sobrevivência proporcionais para dados discretos com presença de censura
(Universidade Federal de São Carlos, 2023-04-25)
Survival models, in their majority, consider continuous survival times. However, in several studies these times are discrete, and in some occasions, it is not advisable to use a continuous model to analyze discrete data. ...
Família Kumaraswamy-G para analisar dados de sobrevivência de longa duração
(Universidade Federal de São Carlos, 2015-02-25)
In survival analysis is studied the time until the occurrence of a particular event of interest and in the literature, the most common approach is parametric, where the data follow a specific probability distribution. ...
Métodos de Monte Carlo Hamiltoniano na inferência Bayesiana não-paramétrica de valores extremos
(Universidade Federal de São Carlos, 2015-03-09)
In this work we propose a Bayesian nonparametric approach for modeling extreme value data. We treat the location parameter _ of the generalized extreme value distribution as a random function following a Gaussian process ...