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.
In Chapter 4, we discuss and prove the consistency and asymptotic normality of maximum likelihood estimate to the exponential models.
The weak consistence and the asymptotic normality of the robust M-estimate of the unknown function are given, and the weak consistence of the robust M-estimate of the unknown parameter is established.
In this paper, we prove the strong consistency of the estimate, its efficiency asymptotic normality is discussed, too.
The strong consistency, asymptotic normality and asymptotic efficiency of these methods are proved.
