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首页> 外文期刊>Geochemistry International >Equivalence Assessment of Multiple Datasets by Quantile-Value Diagram (QVD) for Detection of Significant Shifts (Case Study: Geochemical Datasets from Hanza Region, Kerman, Iran)
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Equivalence Assessment of Multiple Datasets by Quantile-Value Diagram (QVD) for Detection of Significant Shifts (Case Study: Geochemical Datasets from Hanza Region, Kerman, Iran)

机译:分位数值图(QVD)对多个数据集的等价评估,用于检测重大班次(案例研究:来自哈氏地区的地球化学数据集,Kerman,伊朗)

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The purpose of equivalence assessement is to recognize a significant shift between values of the same variables (elements in geochemical surveys) in two datasets. To merge two or more independent datasets that are somehow linked together to create a new integrated dataset, the significance of the difference between datasets must be determined. Merging data originated from two or more geochemical surveys can be highly beneficial to establish geochemical maps with an increased resolution and/or a covered area. Different methods of sampling, preparation and analysis are being used in various geochemical surveys which have a major impact on the measurement of the concentration of elements, and there might be a systematic shift in the concentration of the same elements. Therefore, studying the presence of a significant shift between datasets, and leveling them as a pre-processing stage is essential to combine geochemical data and provide an integrated map of a few independent surveys. While combining datasets to provide integrated maps, not assessing the equivalence and leveling the datasets leads to invalid maps. Determining the equivalence assessment between datasets is done by different methods. Quantile-Quantile Dispersion Diagram and Multiple Frequency Histogram methods have already been introduced by researchers. These methods are visual and dependent on expert judgment. In this study the Fisher test, T-student test, and Quantile-Value Diagram (QVD) are introduced to assess the equivalence between two datasets for the first time. Fisher and T-student tests are applied to compare the variance and average of the same elements in two datasets. In this study, we propose an original method for assessing the equivalence. QVD is introduced as a new method of determining the shift between multiple datasets. The case study is the equivalence assessment and shift determination between two independent geochemical surveys in north of Sarduiyeh and south of Rayen sheets (Hanza, southern part of Urmia-Dokhtar metalogenic belt, Iran). The equivalence assessment was performed for twelve elements including Zn, Pb, Ag, Ni, Bi, Cu, As, Sb, Co, W, Mo, and Mn. Based on Quantile-Quantile Dispersion Diagram and Multiple Frequency Histogram methods, some elements of the two databases were considered as equivalent, but the analysis of QVD method shows a significant shift for them. Fisher and T-student tests confirm the results of QVD. QVD is an exact method for the equivalence assessment that is not dependent on the expert judgment. Eventually, Fisher test, T-student test, and QVD are recommended simultaneously to assess the equivalence between datasets.
机译:等同性评估的目的是识别两个数据集中相同变量的值(地球化学调查中的元素)之间的显着转变。为了合并一个以某种方式链接在一起以创建新的集成数据集的独立数据集,必须确定数据集之间的差异的重要性。合并来自两个或更多地地球化学调查的数据可以非常有利于建立具有增加的分辨率和/或覆盖区域的地球化学图。不同的取样方法,制备和分析用于各种地球化学调查,其对测量元件浓度的主要影响,并且可能存在相同元素的浓度的系统变化。因此,研究数据集之间的显着偏移,并将其平整为预处理阶段是必须组合地球化学数据的必要条件,并提供几种独立调查的集成图。同时组合数据集以提供集成的地图,而不是评估等效项,并调平数据集会导致无效映射。确定数据集之间的等价评估由不同的方法完成。研究人员已经引入了定量定量分散图和多频直方图方法。这些方法是视觉和依赖专家判断。在这项研究中,引入Fisher测试,T-Custoring测试和分位数值图(QVD)以首次评估两个数据集之间的等效。 Fisher和T-Custor测试应用于比较两个数据集中相同元素的方差和平均值。在本研究中,我们提出了一种用于评估等价的原始方法。 QVD被引入为确定多个数据集之间的偏移的新方法。案例研究是Sarduiyeh北部和Rayen床北部两种独立地球化学调查的等价评估和转变确定(Hanza,urmia-dokhtar Metalogenic Belt,Iran)。对12个元素进行等效评估,包括Zn,Pb,Ag,Ni,Bi,Cu,Sb,Co,Co,W,Mo和Mn。基于定量位分散图和多个频率直方图方法,两个数据库的一些元素被认为是等效的,但QVD方法的分析显示了它们的显着转变。 Fisher和T学生测试确认了QVD的结果。 QVD是不依赖于专家判断的等效评估的精确方法。最终,建议同时使用Fisher测试,T-Custoric测试和QVD来评估数据集之间的等价。

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