Fort H. Forecasting with Maximum Entropy 2022

Textbook in PDF format

The common thread throughout the book is how the flux of information controls as well as serves to predict the dynamics of complex systems. Information emerges as a key concept across biological systems, markets and physical systems. Hence, to provide an integrative perspective for the interface between physics, biology and economics we rely on information theory (IT), which, since its formulation by Claude Shannon in the late 1940s, has emerged as a key conceptual framework across different scientific areas. Along the chapters we will proceed like putting together a puzzle, one piece per chapter1 , and building conceptual bridges between the new piece with the other pieces that have already been assembled.
Entropy as missing information: from Shannon’s information theory to Jaynes’ maximum entropy principle
The synthesis of information theory and thermodynamics: Shannon entropy and Boltzmann entropy are the same thing
Elements of physical biology: the Lotka–Volterra equations
Economics as physics, economics as biology
Inferring effective interaction matrices through MaxEnt
Early warning indications of species crashes from effective intraspecific interactions in tropical forests
Modelling markets as ecosystems with the help of maximum entropy