Heteroscedastic Nonlinear Regression Models |
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Authors: | Edilberto Cepeda Cuervo Jorge Alberto Achcar |
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Affiliation: | 1. Departamento de Estadística , Universidad Nacional de Colombia , Bogotá, Colombia ecepeda@unal.edu.co;3. Departamento de Medicina Social, FMRP , Universidade de S?o Paulo , S?o Paulo, Brazil |
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Abstract: | A very general class of models for discrete data is introduced that includes log-linear, linear, and product models as special cases. Maximum likelihood equations are developed to yield a Fisher scoring algorithm for fitting the models to both complete and incomplete data. Two examples serve to underscore the usefulness of these models. |
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Keywords: | Bayesian analysis Heteroscedasticity MCMC algorithm Nonlinear regression Parameter estimation |
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