Data Science for Complex Systems
Data Science for Complex Systems
K. Shuvo Bakar, University of Sydney
Anirban Chakraborti, BML Munjal University, India
$69.99
USDMany real-life systems are dynamic, evolving, and intertwined. Examples of such systems displaying 'complexity', can be found in a wide variety of contexts ranging from economics to biology, to the environmental and physical sciences. The study of complex systems involves analysis and interpretation of vast quantities of data, which necessitates the application of many classical and modern tools and techniques from statistics, network science, machine learning, and agent-based modelling. Drawing from the latest research, this self-contained and pedagogical text describes some of the most important and widely used methods, emphasising both empirical and theoretical approaches. More broadly, this book provides an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists who require effective analysis of large quantities of data, whether that be related to social networks, financial markets, economies or other types of complex systems.
- Presents classic results in an accessible manner alongside more recent advances, enabling readers without specialized training in complex systems to get up to speed
- Supported by examples throughout that demonstrate the theory and explore applications across a range of disciplines
- Describes a wide range of analytical methodologies which can be applied to complex economic and social systems
Reviews & endorsements
'Complex systems are a subject of popular interest thanks to the efforts of both academics and industry researchers during the last few years, and the 2021 Nobel Prize in Physics. This book is timely and it gives a comprehensive view of complex systems with an emphasis on data-driven contributions, ranging from economic and financial aspects to broader social science applications. Reading this book is a pleasure, and it provides a solid and robust understanding of the key topics in the field. This is a 'must -read for anybody interested in complex systems' and I strongly recommend having it on your shelf!' Tiziana Di Matteo, King's College London, Complexity Science Hub Vienna, and Enrico Fermi Research Centre (CREF)
Product details
May 2023Hardback
9781108844796
289 pages
251 × 176 × 21 mm
0.7kg
Not yet published - available from February 2025
Table of Contents
- Preface
- Part I. Introduction:
- 1. Facets of complex systems
- Part II. Heterogeneity and Dependence:
- 2. Quantifying heterogeneity: Classical and Bayesian statistics
- 3. Statistical analyses of time-varying phenomena
- Part III. Patterns and Interlinkages:
- 4. Pattern recognition in complex systems: machine learning
- 5. Interlinkages and heterogeneity: network theory. Part IV. Emergence: from Micros to Macro:
- 6. Interaction and emergence: agent-based models
- 7. Epilogue
- References
- Index.
