Methods for the Analysis of Asymmetric Proximity Data

This book offers a comprehensive guide to techniques for analyzing asymmetric proximity data, making it essential for researchers in various fields.

This book serves as an accessible introduction to asymmetric multidimensional scaling, cluster analysis, and related methodologies. It provides practical guidelines for applying these techniques to asymmetric one-mode two-way and three-way data. A key aim is to equip applied researchers with a comprehensive toolkit of methods and algorithms for effectively representing and clustering asymmetric relationships.

Data often involves measurements of asymmetric relationships between pairs of objects from a specified set, which may include subjects, variables, or attributes, and is typically organized in one or more matrices. The methodologies discussed in Methods for the Analysis of Asymmetric Proximity Data find relevance across various fields, including psychology, sociology, marketing research, and linguistics. More recent applications have emerged in technological domains such as cybernetics, air traffic control, robotics, and network analysis.

The algorithms presented are illustrated through carefully selected examples, complemented by extensive data analyses. Additionally, the book reviews specialized statistical software that can facilitate these applications. This monograph is a valuable resource for readers seeking a thorough and current reference on methods for analyzing asymmetric proximity data.