Forecasting with Maximum Entropy: The interface between physics, biology, economics and information theory...

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Hugo Fort (Republic University, Montevideo, Uruguay)

Forecasting with Maximum Entropy

The interface between physics, biology, economics and information theory

Hugo Fort (Republic University, Montevideo, Uruguay)

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English

Institute of Physics Publishing
25 November 2022

Information theory; Statistical physics; Ecological science, the Biosphere

Series: IOP ebooks

This book aims at providing a unifying framework, based on Information Entropy and its maximization, to connect the phenomenology of evolutionary biology, community ecology, financial economics, and statistical physics. This more comprehensive view, besides providing further insight into problems, enables problem-solving strategies by applying proven methods in one discipline to formally similar problems in other areas. The book also proposes a forecasting method for important practical problems in these disciplines and is directed to researchers, students and practitioners working on modelling the dynamics of complex systems.

The common thread is how the flux of information both controls and serves to predict the dynamics of complex systems. It is shown how maximizing the Shannon information entropy allows one to infer a central object controlling the dynamics of complex systems, such as ecosystems or markets. The resulting models, which are known as pairwise maximum-entropy models, can be used to infer interactions from data in a wide variety of systems. Here, two examples are analysed in detail. The first is an application to conservation ecology, namely the issue of providing early warning indicators of population crashes of species of trees in tropical forests. The second is about forecasting the market values of firms through evolutionary economics. An interesting lesson is that PME modelling often produces accurate predictions despite not incorporating explicit interaction mechanisms.

Key features

Written to be suitable for a broad spectrum of readers and assumes little mathematical specialism. Includes pedagogical features: Worked examples, case studies and summaries. The interdisciplinary approach builds bridges between disciplines. Oriented to solve practical problems. Includes a combination of analytical derivations and numerical simulations with experiments

By: Hugo Fort (Republic University Montevideo Uruguay)
Imprint: Institute of Physics Publishing
Country of Publication: United Kingdom
Dimensions: Height: 254mm, Width: 178mm, Spine: 17mm
ISBN: 9780750339292
ISBN 10: 0750339292
Series: IOP ebooks
Pages: 220
Publication Date: 25 November 2022
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

1 Entropy As Missing Information: From Shannon´S Information Theory to Jaynes´ Maximum Entropy Principle 2 The Synthesis of Information Theory and Thermodynamics: Shannon’s Entropy and Boltzmann’s Entropy are the Same Thing 3 Elements of Physical Biology: Population Dynamics In Ecology And Evolution 4 Economics as Physics, Economics As Biology 5 Inferring Effective Interaction Matrices Through Maxent 6 Early Warning Indications of Species Crashes From Effective Intraspecific Interactions In Tropical Forests 7 Modeling Markets as Ecosystems With The Help Of Maximum Entropy A A Metric to Measure the Pace of Change of the Payoff Matrix

Hugo Fort is a Professor at the Physics Department of the Faculty of Sciences of the Republic University (Montevideo, Uruguay) and Head of the Complex System Group. He earned his PhD in physics from the Autonomous University of Barcelona in 1994 and his early research fields included quantum field theory and high energy physics. Since 2001 his scientific interests evolved from theoretical physics to complex systems and mathematical modelling applied to problems in biology, with a focus on ecology & evolution. The main goal of his research is to develop quantitative methods and tools for ecology and evolution problems. He is currently involved in different projects ranging from agronomic science to ecology and from evolution to game theory. He has published in a wide variety of scientific journals as well as chapters in books covering several different areas: agriculture sciences, applied mathematics, biology, ecology, physics and social sciences.