Multivariate Mean Parameter Estimation by Using a Partly Exponential Model
提出一类部分指数模型用于多元响应数据的回归分析，该模型以响应均值和形状参数为参数，包含广义线性误差模型和指数分散模型作为特例，并研究了均值参数的最大似然估计与广义估计方程的关系。
SUMMARY A class of partly exponential models is proposed for the regression analysis of multivariate response data. The class is parameterized in terms of the response mean and a general shape parameter. It includes the generalized linear error model and exponential dispersion models as special cases. Maximum likelihood equations for mean parameters are shown to be of the same form as certain generalized estimating equations, and maximum likelihood estimates of mean and shape parameters are asymptotically independent. Some results are given on the efficiency of the estimating equation procedure under misspecification of the response covariance matrix.