2024/01/23 by Jan Graffelman, Graffelman, Jan
Agricultural and Biological Sciences · Decision Sciences · Mathematics · #62 #Computation (stat.CO) #FOS: Computer and information sciences #G.3 #Optimal Experimental Design Methods #Sensory Analysis and Statistical Methods #Statistical Methods and Applications
paper · pdf · doi:10.48550/arxiv.2401.12730
openalex publication_date 2024/01/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
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.