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Data Analysis for Complex Systems

A Linear Algebra Approach

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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

Informations bibliographiques

décembre 2040, env. 168 Pages, Primers in Complex Systems, Anglais
University Presses
978-0-691-13918-0

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