Data Science for Complex Systems

Author:   Anindya S. Chakrabarti (Indian Institute of Management Ahmedabad) ,  K. Shuvo Bakar (University of Sydney) ,  Anirban Chakraborti (BML Munjal University, India)
Publisher:   Cambridge University Press
ISBN:  

9781108844796


Pages:   289
Publication Date:   25 May 2023
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Data Science for Complex Systems


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Author:   Anindya S. Chakrabarti (Indian Institute of Management Ahmedabad) ,  K. Shuvo Bakar (University of Sydney) ,  Anirban Chakraborti (BML Munjal University, India)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Dimensions:   Width: 17.60cm , Height: 2.10cm , Length: 25.10cm
Weight:   0.700kg
ISBN:  

9781108844796


ISBN 10:   1108844790
Pages:   289
Publication Date:   25 May 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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.

Reviews

'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)


Author Information

Anindya S. Chakrabarti is an Associate Professor of Economics and UTI Chair of Macroeconomics at the Indian Institute of Management Ahmedabad. His main research interests are macroeconomics, big data in economics, time series econometrics, network theory and complex systems. K. Shuvo Bakar is Senior Lecturer at the University of Sydney. His research interests are Bayesian modelling and computation to reduce uncertainty in inferential statements. He works on statistical machine learning methods and applications to real-life data-driven problems. Anirban Chakraborti is Dean of Research at the School of Engineering and Technology at BML Munjal University, India. His main research interests lie in the areas of econophysics, data science, quantum physics and nanomaterial science.

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