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A nonparametric bayesian approach for modeling and comparison of functional data
(Universidade Federal de São Carlos, 2022-09-02)
The current advances of technology provides, among other things, several ways of collecting
data, which enlarges the possibility of studying new phenomena. Researches focused on studying
the functional relation between ...
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 ...
Estimação do número de comunidades no modelo estocástico de blocos com correção de grau
(Universidade Federal de São Carlos, 2022-12-14)
The stochastic block model (SBM) is a random graph model that splits the set of vertices into blocks, and
the probability connection between each pair of vertices depends on the blocks to which the vertices
belong. The ...
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 ...
Testes bayesianos em ensaios clínicos
(Universidade Federal de São Carlos, 2022-02-22)
In this thesis, we propose two new Bayesian approaches for equivalence hypotheses testing for proportions and prove that these Bayesian hypotheses tests are equivalent. These Bayesian methodologies applied to equivalence ...
Poincaré recurrence times in stochastic mixing processes
(Universidade Federal de São Carlos, 2022-02-17)
In the context of the discrete-time stochastic processes, this thesis presents new results on Poincaré recurrence theory. After a complete review of recent results, we present a new theorem on the exponential approximations ...
Extensões do resíduo quantílico
(Universidade Federal de São Carlos, 2022-12-20)
Regression models have profound importance in analyses that aim to investigate the relationship between a dependent variable and a set of predictor variables. The diagnostic analysis is a fundamental step in validating a ...