Tesis
Modelos de regressão binomial correlacionada
Fecha
2012-05-18Registro en:
PIRES, Rubiane Maria. Modelos de regressão binomial correlacionada. 2012. 148 f. Tese (Doutorado em Ciências Exatas e da Terra) - Universidade Federal de São Carlos, São Carlos, 2012.
Autor
Pires, Rubiane Maria
Institución
Resumen
In this thesis, a class of correlated binomial regression models is proposed. The model is based on the generalized binomial distribution proposed by Luceño (1995) and Luceño & Ceballos (1995). The regression structure is modeled by using four different link functions and the dependence between the Bernoulli trials is modeled by using three different correlation structures. A data augmentation scheme is used in order to overcome the complexity of the mixture likelihood. Frequentist and Bayesian approaches are used in the model fitting process. A diagnostics analysis is provided in order to check the underlying model assumptions and to identify the presence of outliers and/or influential observations. Simulation studies are presented to illustrate the performance of the developed methodology. A real data set is analyzed by using the proposed models. Also the correlated binomial regression models is extended to include measurement error in a predictor. This new class of models is called additive normal structure correlated binomial regression models. The inference process also includes a data augmentation scheme to overcome the complexity of the mixture likelihood.