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 /

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 /

Orientador: Fernando Antonio Moala === Abstract: 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 of its parameters based on sampl...

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Bibliographic Details
Main Author: Gianfelice, Paulo Roberto de Lima.
Other Authors: Universidade Estadual Paulista "Júlio de Mesquita Filho" Faculdade de Ciências e Tecnologia.
Format: Others
Language:Portuguese
Published: Presidente Prudente, 2020
Subjects:
Censored and covariate data
Maximum likelihood and bayesian estimation
Extensions for Exponential Geometric distribution
Statistical simulation
Dados censurados e covariados
Estimação de máxima verossimilhança e bayesiano
Extensões para a distribuição Exponencial Geométrica
Simulação estatística
Online Access:http://hdl.handle.net/11449/192924

Internet

http://hdl.handle.net/11449/192924

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