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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 ...
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 ...
Modelagem via redes neurais de dados de sobrevivência de longa duração com dispersão não observada
(Universidade Federal de São Carlos, 2023-12-08)
Traditional models in survival analysis assume that every subject will eventually experience the event of interest in the study, such as death or disease recurrence, so the survival function is said to be proper. Cure rate ...
Uma abordagem estatística para a análise dos resultados das eleições presidenciais
(Universidade Federal de São Carlos, 2024-01-15)
Multiparty data has characteristics that make it compositional data such as a constant sum of components and a limited space known as simplex. Thus, the purpose of the work is to develop a methodology to analyze multi-party ...
Método bagging para aprimoramento de previsões de séries temporais
(Universidade Federal de São Carlos, 2021-10-22)
Different methodologies are proposed and explored aiming to reduce time series forecasting
error. A promising approach consists in combining different forecasts from different models
in order to get a better accuracy, ...
A robust lasso regression for linear mixed-effects models with diagnostic analysis
(Universidade Federal de São Carlos, 2021-10-22)
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 ...
Observações atípicas em alta dimensão
(Universidade Federal de São Carlos, 2022-09-15)
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 ...
Bayesian inference for term structure models
(Universidade Federal de São Carlos, 2022-06-09)
We explore recent advances in Bayesian methods in order to estimate the Vasicek, CIR and
dynamic Nelson-Siegel (DNS) models for term structure of interest rates. The models are
specified as state space time series. The ...
Lambert-F univariate distributions for asymmetrical data
(Universidade Federal de São Carlos, 2021-12-16)
In this dissertation, we propose new univariate continuous distributions for modeling asymmetrical data. Initially, starting from a non-linear parametric transformation of an uniform random variable, we propose a new ...
Métodos de estimação baseados em modelos na presença de dados faltantes
(Universidade Federal de São Carlos, 2022-10-14)
The missing data are observations that should have been made, but were not for some reason,
thus reducing the ability to understand the nature of the phenomenon, in addition to making it
difficult to extract information ...