The Structural Representation of Proximity Matrices with MATLAB

Hubert (University of Illinois), Arabie (Rutgers), and Meulman (Leiden University) demonstrate how to find and fit structures of proximity matrices computationally with sixty-five functions for Matlab. After explaining linear unidimensional scaling (LUS) and circular scaling (CUS), the monograph walks through ultrametric and additive tree structures for representing the pattern of information potentially present in a single numerically given proximity matrix. The text can also be used as supplementary material for a second year graduate methodology course in the behavioral and social sciences. Annotation c2006 Book News, Inc., Portland, OR (booknews.com)

Lawrence Hubert is Professor of Psychology and Statistics at the University of Illinois Urbana-Champaign.Phipps Arabie is Professor of Management and Psychology at Rutgers University.Jacqueline Meulman is Professor of Applied Data Theory in the Faculty of Social and Behavioral Sciences of Leiden University, The Netherlands.