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Regressão binária nas abordagens clássica e bayesiana
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus 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 ...
Redes Bayesianas para classificação com aprendizado via scoring and restrict: método, aplicação e comparação com métodos tradicionais
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Ciências Fisiológicas - PIPGCFCâmpus São Carlos, 2021-04-05)
This work is an investigation towards the behavior of discrete Bayesian Networks (BN) which aims to solve classification problems. This methodology is based on graphs and probability theories, and
it is defined to be ...
A distribuição normal-valor extremo generalizado para a modelagem de dados limitados no intervalo unitário (0, 1)
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2019-06-28)
In this research a new statistical model is introduced to model data restricted in the continuous interval (0,1). The proposed model is constructed under a transformation of variables, in which the transformed variable is ...
Model parameter identification and model class selection in piezoelectric energy harvester based on bayesian inference
(Universidad de Chile, 2020)
The model updating of the electro-mechanical properties of Piezoelectric Energy Harvesters (PEHs) using experimental data within a Bayesian inference setting is discussed. The implementation requires: a predictive model ...
Bayesian parameter estimation using amortized variational inference.
(Universidad de Concepción.Departamento de Ingeniería Informática y Ciencias de la ComputaciónDepartamento de Ingeniería Informática y Ciencias de la Computación., 2020)
Through the use of models, it is possible to express information about a process or
data being analyzed. These models seek to explain or predict the process of interest.
Models with a known and fixed number of parameters, ...
Bayesian and classical inference for extensions of Geometric Exponential distribution with applications in survival analysis under the presence of the data covariated and randomly censored
(Universidade Estadual Paulista (Unesp), 2020-02-26)
This work presents a study of probabilistic modeling, with applications to survival analysis, based on a probabilistic model called Exponential Geometric (EG), which o ers great exibility for the statistical estimation ...
Redes probabilísticas de K-dependência para problemas de classificação binária
(Universidade Federal de São CarlosBRUFSCarPrograma de Pós-Graduação em Estatística - PPGEs, 2012-02-28)
Classification consists in the discovery of rules of prediction to assist with planning and decision-making, being a continuously indispensable tool and a highly discussed subject in literature. As a special case in ...
Algumas extensões da distribuição Birnbaum-Saunders: uma abordagem bayesiana
(Universidade Federal de São CarlosBRUFSCarPrograma de Pós-Graduação em Estatística - PPGEs, 2012-01-09)
The Birnbaum-Saunders Distribution is based on an physical damage that produces the cumulative fatigue materials, This fatigue was identified as an important cause of failure in engineering structures. Recently, this model ...