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Mostrando ítems 91-96 de 96
Análises Bayesiana para o modelo de regressão Birnbaum-Saunders com zeros ajustados
(Universidade Federal de São Carlos, 2021-08-11)
Modeling based on the Birnbaum-Saunders distribution has received considerable attention
in recent years. In this work we consider the reparametrized Birnbaum-Saunders
distribution with zero-adjusted (ZARBS) (SANTOS-NETO ...
Equações diferenciais estocásticas e as estratégias de hedging no mercado de opções
(Universidade Federal de São Carlos, 2022-06-24)
The Stochastic Differential Equation models (SDEs) assume an important role in finances. The major part of these models try to help the investors with the risk management of the financial activities and they use SDEs for ...
Bayesian variable selection using data driven reversible jump: an application to schizophrenia data
(Universidade Federal de São Carlos, 2021-12-17)
Symptom based diagnosis are known to be limited specially concerning complex disorders such as schizophrenia. Modern attempts in providing predictive risk for such disease, to assist existing diagnosis tools, integrate ...
Inferência Bayesiana em modelos de volatilidade estocástica na média utilizando o método de Monte Carlo Hamiltoniano em variedade Riemanniana
(Universidade Federal de São Carlos, 2024-02-21)
This paper considers the stochastic volatility in mean model, where the conditional distribution of the data belongs to the mixed-scale normal family for modeling financial time series. This model class is more robust in ...
Modelo hierárquico Bayesiano não paramétrico aplicado em modelagem de tópicos
(Universidade Federal de São Carlos, 2024-02-19)
Given the growing need and importance of analyzing textual data in the field of artificial intelligence, models that can better understand human language and deal with unstructured data are increasingly relevant gains. In ...
Rumour spreading in dynamic random graphs
(Universidade Federal de São Carlos, 2024-02-19)
We study rumour spreading in dynamic random graphs. Starting with a single informed vertex, the information flows until it reaches all the vertices of the graph (completion), according to the following process. At each ...