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Métodos Bayesianos para seleção de modelos de mistura de distribuições normais e t de Student assimétricas
(Universidade Federal de São Carlos, 2023-06-28)
In this work, we consider mixture models whose components of the mixture are modeled by the skew normal and skew t distributions. For the estimation of these skew mixtures models, we used a Bayesian approach, via Markov ...
Modelos de fração de cura com fragilidade inflacionado de zero sob diferentes esquemas de ativação
(Universidade Federal de São Carlos, 2023-08-22)
In this doctoral thesis, the proposed methodology is based on zero-inflated survival data to deal with situations where there is a fraction of inflated (or adjusted) zeros and cured cases considering different activation ...
Modelos Lomax assimétricos: uma nova abordagem para a classificação de dados binários desbalanceados
(Universidade Federal de São Carlos, 2023-05-17)
Imbalanced data refers to a dataset where one class has significantly fewer observations than the other class. This can lead to poor performance of both machine learning algorithms and statistical models, since most of ...
Inferência Bayesiana para modelos de volatilidade estocástica baseados em mistura de escala da distribuição normal assimétrica
(Universidade Federal de São Carlos, 2023-02-28)
This dissertation aims to evaluate and compare the performance of the No-U-Turn Sampler
(NUTS) algorithm, implemented in the Stan software, in estimating the parameters of stochastic
volatility models with leverage based ...
Using VAE for incomplete educational data
(Universidade Federal de São Carlos, 23-03-13)
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 ...
Bayesian estimation of dynamic mixture models by wavelets
(Universidade Federal de São Carlos, 2023-04-20)
Gaussian mixture models are used successfully in various statistical learning applications. The good results provided by these models encourage several generalizations of them. Among possible adaptations, one can assume a ...
Teoremas limite para variáveis aleatórias de Bernoulli dependentes
(Universidade Federal de São Carlos, 2023-03-22)
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 ...
Small and time-efficient distribution-free predictive regions
(Universidade Federal de São Carlos, 2023-05-02)
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 ...
Inferência em redes aleatórias com pesos discretos
(Universidade Federal de São Carlos, 2023-04-04)
Random networks have been widely used to describe interactions between objects, including interpersonal relationships between individuals. One of the most important features of networks is the presence of communities, which ...