Data Analysis for Complex Systems

A Linear Algebra Approach

von Daniel Rockmore, Scott Pauls, Greg Leibon

168 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

The analysis of complex systems-from financial markets and voting patterns to ecosystems and food webs-can be daunting for newcomers to the subject, in part because existing methods often require expertise across multiple disciplines. This book shows how a single technique-the partition decoupling method-can serve as a useful first step for modeling and analyzing complex systems data. Accessible to a broad range of backgrounds and widely applicable to complex systems represented as high-dimensional or network data, this powerful methodology draws on core concepts in network modeling and analysis, cluster analysis, and a range of techniques for dimension reduction. The book explains these and other essential concepts and provides several real-world examples to illustrate how a data-driven approach can illuminate complex systems.- Provides a comprehensive introduction to modeling and analysis of complex systems with minimal mathematical prerequisites- Focuses on a single technique, thereby providing an easy entry point to the subject- Explains analytic techniques using actual data from the social sciences- Uses only linear algebra to model and analyze large data sets- Includes problems and real-world examples- An ideal textbook for students and invaluable resource for researchers with a wide range of backgrounds and preparation- Proven in the classroom

• Themen: Mathematik und Naturwissenschaften Physik Mathematische / Computergestützte / Theoretische Physik
• ISBN: 9780691139180
• Sprache: Englisch
• Erscheinungsdatum: 25.12.1940
• Verlag: Princeton University Press