In this paper we discuss the convergence of the EM algorithm for iterative computation of maximum likelihood estimates when the observations can be viewed as incomplete data.
本文讨论EM算法的收敛性，其中EM算法是不完全数据处理中的一类重要的参数估计的迭代算法。
The tendency check, goodness of fit check, maximum likelihood estimates (MLE) of the parameters and MTBF for AMSAA model are presented.
给出了趋势检验、AMSAA模型的拟合优度检验及模型参数的极大似然估计方法。
The tendency check, goodness of fit check, maximum likelihood estimates (MLE) of the parameters and MTBF for AMSAA model are presented.
给出了趋势检验、AMSAA模型的拟合优度检验及模型参数的极大似然估计方法。
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