The model parameters were estimated by a maximum likelihood algorithm, which maximizes the likelihood of the observed data.
采用最大似然估计算法,对模型中的隐含参数进行了估计。
The maximum likelihood estimators(MLE) of means and standard deviations, and the asymptotic distribution of likelihood ratio statistic were given.
给出了正态总体均值和标准差的最大似然估计(M LE),似然比检验统计量及其渐近分布等结果。
Meanwhile, when there no trap happens, a new adaptive stopping rule for CVA is proposed which is based on comparing the maximum likelihood path with the best maximum likelihood tail-biting path.
在没有循环陷阱产生的情况下,新算法比较当前迭代中最大似然路径和已经发现的最优咬尾路径是否相同来自适应终止迭代。
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