Extensions of earlier algorithms and enhanced visualization techniques for approximating a correlation matrix are presented. The visualization problems that result from using column or colum--and--row adjusted correlation matrices, which give numerically a better fit, are addressed. For visualization of a correlation matrix a weighted alternating least squares algorithm is used, with either a single scalar adjustment, or a column-only adjustment with symmetric factorization; these choices form a compromise between the numerical accuracy of the approximation and the comprehensibility of the obtained correlation biplots. Some illustrative examples are discussed.

翻译：本文提出了对早期算法的扩展及增强的可视化技术，用于逼近相关矩阵。针对采用列调整或列-行调整相关矩阵（虽然能在数值上实现更优拟合）所引发的可视化问题进行了探讨。在相关矩阵的可视化过程中，采用了加权交替最小二乘算法，该算法可选择单标量调整或结合对称分解的仅列调整方案；这些选择在逼近的数值精度与所得相关双标图的可理解性之间形成折中。文中还讨论了一些具有说明性的实例。