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Enriched biplots for canonical correlation analysis

机译:丰富的双线图用于规范相关分析

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This paper discusses biplots of the between-set correlation matrix obtained by canonical correlation analysis. It is shown that these biplots can be enriched with the representation of the cases of the original data matrices. A representation of the cases that is optimal in the generalized least squares sense is obtained by the superposition of a scatterplot of the canonical variates on the biplot of the between-set correlation matrix. Goodness of fit statistics for all correlation and data matrices involved in canonical correlation analysis are discussed. It is shown that adequacy and redundancy coefficients are in fact statistics that express the goodness of fit of the original data matrices in the biplot. The within-set correlation matrix that is represented in standard coordinates always has a better goodness of fit than the within-set correlation matrix that is represented in principal coordinates. Given certain scalings, the scalar products between variable vectors approximate correlations better than the cosines of angles between variable vectors. Several data sets are used to illustrate the results.
机译:本文讨论了通过规范相关分析获得的组间相关矩阵的双线图。结果表明,可以用原始数据矩阵的情况表示来丰富这些双线图。通过将典型变量的散点图叠加在组间相关矩阵的双点图上,可以获得在广义最小二乘意义上最佳的案例表示。讨论了规范相关分析中涉及的所有相关和数据矩阵的拟合统计优度。结果表明,充分性和冗余系数实际上是统计数据,表示双图中原始数据矩阵的拟合优度。用标准坐标表示的组内相关矩阵总是比用主坐标表示的组内相关矩阵具有更好的拟合度。在给定一定比例的情况下,变量矢量之间的标量积近似相关性要好于变量矢量之间角度的余弦值。使用几个数据集来说明结果。

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