The strong consistency, asymptotic normality and asymptotic efficiency of these methods are proved.

我们研究了这些方法的强相合性，渐近正态性和渐近有效性。

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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。

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The consistency and asymptotic normality behaviors are also investigated for the estimators.

我们也研究了估计的一致性和渐近正态性质。

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