本文构造了非线性模型中参数的经验欧氏似然比统计量，并证明了该似然估计的强相合性和渐近正态性。
In this paper, empirical Euclidean likelihood ratio statistics are constructed for parametric in a nonlinear model. And prove strong consistency and asymptotic normality of the estimation.
本文证明了这种估计的强相合性，并讨论了其优效渐近正态性。
In this paper, we prove the strong consistency of the estimate, its efficiency asymptotic normality is discussed, too.
并且证明了在正态分布的假设下，该总体平均因果效应的极大似然估计是相合无偏且渐近正态的。
The maximum likelihood estimator for population average treatment effect is proved to be consistent, unbiased and asymptotically normal.
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