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Tong et al. [33] considered consistency and normality of HD estimators for the partial linear regression model.
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Liang and Jing [10] established the consistency, uniform consistency, and asymptotic normality of g n (x) under negatively associated (NA) samples.
Results on ε n k being assumed to be independent, consistency and asymptotic normality have been investigated by Georgiev [4] and Müller [5] among others.
The consistency and asymptotic normality of the estimator are derived.
they derived the consistency and asymptotic normality of the estimation.
The consistency and asymptotic normality of both types of estimates are proved.
Asymptotic properties, including strong consistency and asymptotic normality, are also established for general multi-treatment cases.
In this model some limit theorems (strong consistency and asymptotical normality) have been obtained.
The consistency and asymptotic normality of the constrained estimator are established.
Conditions are specified that assure consistency and asymptotic normality of these estimators.
Strong consistency and asymptotic normality of the design are obtained under some widely satisfied conditions.
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