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首页> 外文期刊>International Journal of Statistics and Probability >On Comparison of Local Polynomial Regression Estimators for P=0 and P=1 in a Model Based Framework
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On Comparison of Local Polynomial Regression Estimators for P=0 and P=1 in a Model Based Framework

机译:基于模型框架中P = 0和P = 1的局部多项式回归估计的比较

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This article discusses the local polynomial regression estimator for ?and the local polynomial regression estimator for ?in a finite population. The performance criterion exploited in this study focuses on the efficiency of the finite population total estimators. Further, the discussion explores analytical comparisons between the two estimators with respect to asymptotic relative efficiency. In particular, asymptotic properties of the local polynomial regression estimator of finite population total for ?are derived in a model based framework. The results of the local polynomial regression estimator for ?are compared with those of the local polynomial regression estimator for ?studied by Kikechi et al (2018). Variance comparisons are made using the local polynomial regression estimator ?for ?and the local polynomial regression estimator ?for ?which indicate that the estimators are asymptotically equivalently efficient. Simulation experiments carried out show that the local polynomial regression estimator ?outperforms the local polynomial regression estimator ?in the linear, quadratic and bump populations.
机译:本文讨论了局部多项式回归估计估计,以及局部多项式回归估计器的α?在有限群体中。本研究中阐述的性能标准侧重于有限人口总估计的效率。此外,讨论探讨了两种估计与渐近相对效率之间的分析比较。特别是,有限人口总量的局部多项式回归估计器的渐近性质是基于模型的框架中的。局部多项式回归估计器的结果与局部多项式回归估计器的结果进行比较?由Kikechi等(2018)研究。使用本地多项式回归估计器进行方差比较?对于?和本地多项式回归估算器?对于?这表明估计器是渐近的等效效率。进行的仿真实验表明,局部多项式回归估计器?优于本地多项式回归估算器?在线性,二次和凹凸群中。

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