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Relative vs. absolute statistical analysis of compositions: A comparative study of surface waters of a Mediterranean river

机译:成分的相对绝对统计分析:地中海河流表层水的比较研究

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Most hydrogeological research includes some sort of statistical study, which is generally conducted on the raw measures of chemical variables, though there are several theoretical and practical studies warning against this practice. Arguments refer mainly to the positive character of this type of data, and to the fact that they carry only information about the relative abundance of each component on the whole, what makes techniques based on correlation, like the widely used Principal Component Analysis (PCA), loose their meaning. The solution proposed by Aitchison (1982, Journal of the Royal Statistical Society, Series B 44(2), 139-177)-based on working with log-ratios of observations-is equivalent to define a new distance between compositions and to adapt usual statistical techniques to it. To illustrate its effect, our study compares the performance of the biplot-a PCA graphical technique-according to the usual Euclidean and to the Aitchison distance. The study is conducted on a set of 14 molarities measured monthly through the years 1997-1999 at 30 different stations along the Llobregat River and its tributaries (Barcelona, NE Spain). Ordinary analysis, implicitly based on an Euclidean distance, presents some deficiencies, mainly because it only captures major ion variations and the inferred relationship between them actually depends on other non-relevant variables, such as water mass. An analysis based on compositional distances captures variations of all the ions; it is robust against the inclusion of non-relevant variables in the analysis; and it offers a way to build factors expressed as equilibrium equations. In our case, two promising factors are extracted, showing the different anthropogenic and geological pollution sources of the rivers.
机译:大多数水文地质研究都包括某种统计研究,该研究通常是对化学变量的原始测量进行的,尽管有一些理论和实践研究对此作了警告。参数主要是指此类数据的积极特征,而且它们实际上仅包含有关每个组件的相对丰度的信息,这使基于关联的技术(例如广泛使用的主分量分析(PCA))成为事实。 ,失去其含义。由Aitchison(1982,皇家统计学会杂志,系列B 44(2),139-177)提出的解决方案-基于观察值的对数比率-等同于定义组合之间的新距离并适应通常统计技术。为了说明其效果,我们的研究根据通常的欧几里得距离和Aitchison距离,将biplot(一种PCA图形技术)的性能进行了比较。这项研究是对1997年至1999年期间每月在Llobregat河及其支流(西班牙内布拉斯加州巴塞罗那)的30个不同站点上测得的14种摩尔浓度进行的。隐式基于欧几里得距离的常规分析存在一些缺陷,主要是因为它仅捕获主要的离子变化,并且它们之间的推断关系实际上取决于其他不相关的变量,例如水质量。基于成分距离的分析可捕获所有离子的变化;在分析中不包含无关变量时,它是可靠的;并且它提供了一种构建表达为平衡方程的因子的方法。在我们的案例中,提取了两个有希望的因素,显示了河流的不同人为和地质污染源。

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