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Technical note: A significance test for data-sparse zones in scatter plots

机译:技术说明:对散点图中数据稀疏区域的重要性测试

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Data-sparse zones in scatter plots of hydrological variables can be of interest in various contexts. For example, a well-defined data-sparse zone may indicate inhibition of one variable by another. It is of interest therefore to determine whether data-sparse regions in scatter plots are of sufficient extent to be beyond random chance. We consider the specific situation of data-sparse regions defined by a linear internal boundary within a scatter plot defined over a rectangular region. An Excel VBA macro is provided for carrying out a randomisation-based significance test of the data-sparse region, taking into account both the within-region number of data points and the extent of the region. Example applications are given with respect to a rainfall time series from Israel and also to validation scatter plots from a seasonal forecasting model for lake inflows in New Zealand.
机译:在各种情况下,水文变量散点图中的数据稀疏区可能会引起人们的兴趣。例如,定义明确的数据稀疏区域可能表明一个变量被另一个变量抑制。因此,有必要确定散点图中的数据稀疏区域是否具有足够的程度以超出随机机会。我们考虑由在矩形区域上定义的散点图中的线性内部边界定义的数据稀疏区域的具体情况。提供了一个Excel VBA宏,可对数据稀疏区域进行基于随机性的显着性检验,同时考虑到区域内数据点的数量和区域范围。给出了有关以色列的降雨时间序列的示例应用程序,并且还给出了来自新西兰湖泊流入量季节性预测模型的验证散点图。

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