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使用重复测量估计精密度。

Estimating precision using duplicate measurements.

作者信息

Hyslop Nicole Pauly, White Warren H

机构信息

Crocker Nuclear Laboratory, University of California-Davis, Davis, CA 95616-8569, USA.

出版信息

J Air Waste Manag Assoc. 2009 Sep;59(9):1032-9. doi: 10.3155/1047-3289.59.9.1032.

Abstract

Precision is a concept for which there is no universally accepted metric. Reports of precision vary depending on the formula and inclusion criteria used to calculate them. To properly interpret and utilize reported precisions, the user must understand exactly what the precision represents. This paper uses duplicate Interagency Monitoring of Protected Visual Environments (IMPROVE) measurements to illustrate distinctions among different approaches to reporting precision. Three different metrics are used to estimate the precision from the relative differences between the duplicate measurements: the root mean square (RMS), the mean absolute value, and a percentile spread. Precisions calculated using the RMS relative difference yield wide distributions that tend to overestimate most of the observed differences. Precisions calculated using percentiles of the relative differences yield narrower distributions that tend to fit the bulk of the observed differences very well. Precisions calculated using the mean absolute relative difference lie between the other two precision estimates. All three approaches underestimate the observed differences for a small percentage of outliers.

摘要

精密度是一个尚无普遍接受的衡量标准的概念。精密度报告因用于计算的公式和纳入标准而异。为了正确解释和使用报告的精密度,用户必须确切了解精密度代表什么。本文使用受保护视觉环境的跨部门重复监测(IMPROVE)测量数据来说明报告精密度的不同方法之间的区别。使用重复测量之间的相对差异来估计精密度的三种不同指标:均方根(RMS)、平均绝对值和百分位数范围。使用RMS相对差异计算的精密度产生的分布较宽,往往高估了大多数观察到的差异。使用相对差异百分位数计算的精密度产生的分布较窄,往往能很好地拟合大部分观察到的差异。使用平均绝对相对差异计算的精密度介于其他两种精密度估计值之间。对于一小部分异常值,所有三种方法都会低估观察到的差异。

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