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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 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 ...
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 ...
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 ...
Modelagem de predição de crimes na região metropolitana de São Paulo
(Universidade Federal de São Carlos, 2023-12-13)
The issue of public security is a challenge for Brazilian society, and crime is a major concern for the most populous state in the country, São Paulo. It is always desirable for the public administration to model and predict ...