Likelihood, Quasi-Likelihood and Pseudolikelihood: Some Comparisons
本文通过模拟研究比较了三种分散参数估计量（最大扩展准似然、最大伪似然和最大似然）在联合拟合响应均值和分散模型中的有限样本性质，发现最大扩展准似然估计量在均方误差方面通常更优。
SUMMARY There is considerable interest in the fitting of models jointly to the mean and dispersion of a response. For the mean parameter, the Wedderburn estimating equations are widely accepted. However, there is some controversy about estimating the dispersion parameters. Finite sampling properties of several dispersion estimators are investigated for three models by simulation. We compare the maximum extended quasi-likelihood estimator, the maximum pseudolikelihood estimator and the maximum likelihood estimator, if it exists. Of these estimators, the maximum extended quasi-likelihood estimator is usually superior in minimizing the mean-squared error.