优良抽样设计下总体均值的比率估计
Ratio Estimation for the Population Mean Under Optimal Sampling Design
当研究目标的实际测量具有不可修复的破坏性或耗 资巨大时, 有效的抽样设计将是一项重要的研究课题. 在统计推断方面, 排序集抽样被视为一种更为有效的收集数据的方式. 极值排序集 抽样(ERSS)~是一种改进的排序集抽样. 文章在~ERSS~下研究了总 体均值的比率估计. 以正态分布为例, 比较了简单随机抽样和~ERSS~下比率估计的相对效率. 数值结果表明~ERSS~下的比率估计优于简单随机抽样下的比率估计.
Cost effective sampling is a problem of major concern in some experiments especially when the measurement of the characteristic of interest is costly or painful or time consuming. Ranked set sampling is now regarded as an effective tool in statistical inference. In this article, a modification of ranked set sampling called extremes ranked set sampling (ERSS) is considered for ratio estimation for the population mean. The ratio estimations under ERSS are compared to the corresponding ones under simple random sampling by the relative efficiency for normal data. The simulation results show that the ratio estimations under ERSS are significantly more efficient than the ones under simple random sampling.
排序集抽样 / 极值排序集抽样 / 比率估计. {{custom_keyword}} /
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