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首页> 外文期刊>Journal of Volcanology and Geothermal Research >Predictive regions for geochemical compositional data of volcanic systems
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Predictive regions for geochemical compositional data of volcanic systems

机译：火山系统地球化学组成数据的预测区域

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摘要

In this contribution, the theoretical basis to define predictive regions on multivariate compositional data is applied to, volcanological, geochemical data. The method defines a predictive region based on the calculation of the eigenvalues and eigenvectors of the covariance matrix of a logratio-transformed data set to circumvent the issue of singularity of the covariance matrix of the raw data due to the closure problem. Principal components have been used to reduce dimensionality and produce a 2-D display of the transformed data and the confidence ellipse. The method was tested in a well studied volcanic sequence from Stromboli volcano (The Vancori period) and in the tholeiitic differentiation of Thingmuli volcano represented in the AFM diagram. Results of the first example are strongly consistent with previous works, suggesting that the methodology reproduces the conventional patterns and potentially could help in the search of hidden patterns in noisy data. Results of the second example depict a useful approach for the treatment of volcanic geochemical data when plotted in a ternary diagram.
机译：在这一贡献中，将在多元组成数据上定义预测区域的理论基础应用于火山学，地球化学数据。该方法基于对数变换后的数据集协方差矩阵的特征值和特征向量的计算来定义预测区域，从而避免由于封闭问题而导致原始数据协方差矩阵的奇异性问题。主成分已被用于减小维数并生成转换后的数据和置信椭圆的二维显示。该方法已在斯特伦博利火山（Vancori时期）经过深入研究的火山层序中进行了测试，并在AFM图中以Thingmuli火山的生高分化进行了测试。第一个示例的结果与以前的工作非常吻合，这表明该方法可重现常规模式，并且可能有助于搜索嘈杂数据中的隐藏模式。第二个示例的结果显示了当绘制三元图时处理火山地球化学数据的有用方法。

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