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Inference about the Regression Parameters Using Median-Ranked Set Sampling

机译:使用中位数排序集抽样推断回归参数

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The ranked set samples and median ranked set samples in particular have been used extensively in the literature due to many reasons. In some situations, the experimenter may not be able to quantify or measure the response variable due to the high cost of data collection, however it may be easier to rank the subject of interest. The purpose of this article is to study the asymptotic distribution of the parameter estimators of the simple linear regression model. We show that these estimators using median ranked set sampling scheme converge in distribution to the normal distribution under weak conditions. Moreover, we derive large sample confidence intervals for the regression parameters as well as a large sample prediction interval for new observation. Also, we study the properties of these estimators for small sample setup and conduct a simulation study to investigate the behavior of the distributions of the proposed estimators.
机译:特别地,由于许多原因,排名集样本和中值排名集样本已在文献中广泛使用。在某些情况下,由于数据收集的高昂费用,实验者可能无法量化或测量响应变量,但是对感兴趣的受试者进行排名可能会更容易。本文的目的是研究简单线性回归模型的参数估计量的渐近分布。我们表明,使用弱化排序集抽样方案的这些估计量在弱条件下收敛于正态分布。此外,我们得出回归参数的大样本置信区间以及新观察值的大样本预测区间。此外,我们研究了这些估计量在小样本设置下的性质,并进行了仿真研究以调查所提出的估计量分布的行为。

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