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Processo de Bernoulli correlacionado
(Universidade Federal de São Carlos, 2019-06-28)
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 ...
A distribuição normal-valor extremo generalizado para a modelagem de dados limitados no intervalo unitário (0, 1)
(Universidade Federal de São Carlos, 2019-06-28)
In this research a new statistical model is introduced to model data restricted in the continuous interval (0,1). The proposed model is constructed under a transformation of variables, in which the transformed variable is ...
Modelos COM-Poisson correlacionados
(Universidade Federal de São Carlos, 2019-04-23)
In this thesis two discrete distributions are proposed: Correlated COM-Poisson (CPC) and
Generalized partially correlated COM-Poisson (CPGPC). We have also proposed regression
models for the Generalized partially correlated ...
Contribuições sobre o envelope simulado na análise de diagnóstico em modelos de regressão
(Universidade Federal de São Carlos, 2019-04-30)
The simulated envelope is a diagnostic analysis method used to evaluate the hypothesis about the probability distribution assumed for the response variable in a regression model. In this work, we describe some procedures ...
Modelos de difusão de inovação em grafos
(Universidade Federal de São Carlos, 2019-04-12)
Areas such as politics, economics and marketing are heavily influential in terms of information diffusion. For this reason, several branches of science have studied such phenomena in order to simulate and understand them ...
Modelos não lineares assimétricos com efeitos mistos
(Universidade Federal de São Carlos, 2019-08-02)
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 ...
Neural networks as an optimization tool for regression
(Universidade Federal de São Carlos, 2019-09-02)
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. ...
Métodos de Monte Carlo Hamiltoniano aplicados em modelos GARCH
(Universidade Federal de São Carlos, 2019-04-26)
One of the most important informations in financial market is variability of an asset. Several
models have been proposed in literature with a view of to evaluate this phenomenon. Among
them we have the GARCH models. This ...
Modelo geométrico de ordem k correlacionado
(Universidade Federal de São Carlos, 2019-08-29)
In this work we propose the correlated geometric distribution of order k, k≥1, with parameters π and ρ; π ∈(0,1), max{−1,−1−π π } ≤ρ < 1, as an extension of the generalized geometric distribution proposed by Philippou e ...
Modelos de mistura para avaliação de produtos e serviços
(Universidade Federal de São Carlos, 2019-12-16)
The product (or services) evaluation is a necessity in many steps of the development and release of such producs (services). The product evolution and the market share definition are two steps that evolves some kind of ...