The tendency check, goodness of fit check, maximumlikelihoodestimates (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。
2
In this paper we discuss the convergence of the EM algorithm for iterative computation of maximumlikelihoodestimates 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。
3
The paper estimates both the static and dynamic versions of the model by using simulated maximumlikelihood techniques.