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Statistical distances of measurements for quality control

机译:统计测量距离以进行质量控制

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In widely distributed measurement systems, the first guess for the station measurement quality control is to compare the measurement to the neighbor stations. The basic degree of neighborness is often determined by the inverse distance of the measurement stations. However, this will not be descriptive in statistical sense if the system behind the observations is spatially complex or the sensors suffer from quality issues. This paper suggests a framework for measuring the statistical distance between stations within the system. The measures are developed with an assumption of large-scale observation systems, and therefore the computational and database access requirements are desired to keep as low as possible. The special emphasis of the numerical examples is on the meteorological measurements.
机译:在分布广泛的测量系统中,站测量质量控制的第一个猜测是将测量结果与相邻站进行比较。邻居的基本程度通常由测量站的反距离确定。但是,如果观察背后的系统空间复杂或传感器存在质量问题,则从统计学意义上讲,这不是描述性的。本文提出了一个用于测量系统中站点之间的统计距离的框架。这些措施是在假设大型观测系统的情况下制定的,因此,希望计算和数据库访问需求保持尽可能低的水平。数值示例的特别重点在于气象测量。

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