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Regressão binária nas abordagens clássica e bayesiana
(Universidade Federal de São Carlos, 2016-12-16)
The objective of this work is to study the binary regression model under the frequentist and Bayesian approaches using the probit, logit, log-log complement, Box-Cox transformation and skewprobit as link functions. In the ...
Modelagem da volatilidade em séries temporais financeiras via modelos GARCH com abordagem bayesiana
(Universidade Federal de São Carlos, 2017-07-18)
In the last decades volatility has become a very important concept in the financial area, being used
to measure the risk of financial instruments. In this work, the focus of study is the modeling of
volatility, that ...
Modelos de riscos competitivos no estudo de evasão discente
(Universidade Federal de São Carlos, 2020-02-11)
Dropout is a problem faced by public and private universities. Therefore, the motivation of
this work is to investigate the characteristics of students enrolled in a regular undergraduate
course and verify which one is ...
Essays on bivariate option pricing via copula and heteroscedasticity models: a classical and bayesian approach
(Universidade Federal de São Carlos, 2019-02-15)
This dissertation is composed of two main and independents essays, but complementary. In the first one, we discuss the option price under a bayesian perspective. This essay aims to price and analyze the fair price behavior ...
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 ...
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 ...