Further statistical methods in regression models of the exponential family / Aperfeiçoamento de métodos estatísticos em modelos de regressão da família exponencial
AUTOR(ES)
Alexsandro Bezerra Cavalcanti
DATA DE PUBLICAÇÃO
2009
RESUMO
In this work, we develop three topics related to the exponential family nonlinear regression. First, we obtain the asymptotic covariance matrix of order $n^$, where $n$ is the sample size, for the maximum likelihood estimators corrected by the bias of order $n^$ in generalized linear models, considering the precision parameter known. Second, we calculate an asymptotic formula of order $n^{-1/2}$ for the skewness of the distribution of the maximum likelihood estimators of the mean parameters and of the precision and dispersion parameters in exponential family nonlinear models considering that the dispersion parameter is the same although unknown for all observations. Finally, we obtain Bartlett-type correction factors for the score test in exponential family nonlinear models assuming that the precision parameter is modelled by covariates. Monte Carlo simulation studies are developed to evaluate the results obtained in the three topics.
ASSUNTO(S)
bartlett-type corrections modelos não lineares modelos lineares generalizados generalized linear models coeficiente de assimetria covariance matrix skewness correção tipo-bartlett matriz de covariância estimador de máxima verossimilhança score test teste escore
