The structural representation of proximity matrices with MATLAB

Lawrence Hubert, Phipps Arabie, Jacqueline Meulman9780898716078, 0898716071

The Structural Representation of Proximity Matrices with MATLAB presents and demonstrates the use of functions (by way of M-files) within a MATLAB computational environment to effect a variety of structural representations for the proximity information that is assumed to be available on a set of objects. The representations included in the book have been developed primarily in the behavioral sciences and applied statistical literature (e.g., in psychometrics and classification), although interest in these topics now extends more widely to such fields as bioinformatics and chemometrics.
Throughout the book, two kinds of proximity information are analyzed: one-mode and two-mode. One-mode proximity data are defined between the objects from a single set and are usually given in the form of a square symmetric matrix; two-mode proximity data are defined between the objects from two distinct sets and are given in the form of a rectangular matrix. In addition, there is typically the flexibility to allow the additive fitting of multiple structures to either the given one- or two-mode proximity information.
This book is divided into three main sections, each based on the general class of representations being discussed. Part I develops linear and circular unidimensional and multidimensional scaling using the city-block metric as the major representational device. Part II discusses characterizations based on various graph-theoretic tree structures, specifically those referred to as ultrametrics and additive trees. Part III uses representations defined solely by order properties, particularly emphasizing what are called (strongly) anti-Robinson forms.
Audience This book is intended to provide an applied documentation source for a collection of M-files of use to applied statisticians and data analysts, as well as bioinformaticians, chemometricians, and psychometricians. Industrial engineers, quantitative psychologists, and behavioral and social scientists will also find the content of this book beneficial.