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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 ...
Scalable and interpretable kernel methods based on random Fourier features
(Universidade Federal de São Carlos, 2023-03-29)
Kernel methods are a class of statistical machine learning models based on positive semidefinite kernels, which serve as a measure of similarity between data features. Examples of kernel methods include kernel ridge ...
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 ...
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 ...
Propagação de rumor em uma população cética em N
(Universidade Federal de São Carlos, 2023-03-30)
We consider two models for information propagation in N. In both models, the individuals (one per site of N) have random, independent, and equally distributed radius. At the beginning only the individual at 0 has the ...
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 ...
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 ...