Visualizing Correlation
利用皮尔逊相关系数与夹角余弦的关系，提出一种基于多维缩放的可视化方法，可应用于任意相关系数矩阵，并探讨其在聚类分析中的用途。
The well-known fact that Pearson's product-moment correlation coefficient between two variables is the cosine of the angle between the centered variable profiles suggests a way to visualize correlation. This angular representation of product-moment correlation is automatically displayed in an h-plot. Using ideas from multidimensional scaling, an alternative angular representation of correlation is proposed. The proposed method can be applied to an arbitrary matrix of correlation coefficients. Implications for cluster analysis are considered. The proposed method is applied to correlations of intelligence tests, pit props, and gene expression profiles.