Quasi-Likelihood and Generalizing the Em Algorithm
本文针对数据缺失或不全、完整似然函数不可得的情况，将EM算法推广到基于一般估计函数（特别是拟得分）的估计，用投影拟得分代替E步，M步则求解估计方程。
SUMMARY This paper is concerned with situations in which there are missing or otherwise incomplete data and the full likelihood may not be available. Extensions of the EM algorithm are developed to deal with estimation via general estimating functions and in particular the quasi-score. The E-step is replaced by projecting the quasi-score and the M-step requires the solution of an estimating equation. The standard EM algorithm can be obtained as a particular case if the likelihood is available.