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嵌套广义线性混合模型：经典最佳线性无偏预测方法AI 解读

Summary We introduce a new class of generalized linear mixed models based on the Tweedie exponential dispersion model distributions, accommodating a wide range of discrete, continuous and mixed data. Using the best linear unbiased predictor of random effects, we obtain an optimal estimating function for the regression parameters in the sense of Godambe, allowing an efficient common fitting algorithm for the whole class. Although allowing full parametric inference, our main…

指数离散模型AI 解读

SUMMARY We study general properties of the class of exponential dispersion models, which is the multivariate generalization of the error distribution of Nelder and Wedderburn’s (1972) generalized linear models. Since any given moment generating function generates an exponential dispersion model, there exists a multitude of exponential dispersion models, and some new examples are introduced. General results on convolution and asymptotic normality of exponential dispersion…

广义线性与非线性回归模型的极大似然估计及大样本推断AI 解读

The class of generalized linear models is extended to allow for correlated observations, nonlinear models and error distributions not of the exponential family form. The extended class of models include a number of important examples, particularly of the composite transformational type. Large-sample inference and maximum likelihood estimation for the extended class of generalized linear models are discussed, and the analysis of deviance is generalized to the extended class…