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Multivariate conditional density estimation with copulas
(Universidade Federal de São Carlos, 2021-09-29)
Most machine learning regression models only yield single point estimations for the label of a new observation. However, when dealing with multi-modal or asymmetric distributions, a single point estimate is not enough to ...
Distribuições discretas para duas observações inflacionadas
(Universidade Federal de São Carlos, 2021-07-30)
Count data is often found in many real applications and some observations may occur in the data set in an excessive amount. In many real problems it is quite common for the data set to contain excesses of zero and one ...
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 ...
Considerações e possíveis soluções para o problema da estimação do mínimo populacional com aplicações em dados de terremotos
(Universidade Federal de São Carlos, 2024-04-29)
A myriad of physical, biological and other phenomena are better modeled with semi-infinite distribution families, in which case not knowing the populational minimum becomes a hassle when performing parametric inference. ...
Melhorando a tomada de decisões na construção: Modelagem não paramétrica de atrasos induzidos pelo clima
(Universidade Federal de São Carlos, 2024-05-23)
Effective construction project management faces significant challenges due to frequent delays, many of which are influenced by climatic variables. Anticipating these delays is crucial, and although various methods based ...
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 ...
Análise de agrupamentos para dados espectrais
(Universidade Federal de São Carlos, 2024-03-11)
Spectroscopy is the study that uses techniques to measure the spectrum of electromagnetic radiation, including visible light and radiofrequency, where we search for information such as chemical composition, temperature, ...
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 ...