Forecasting with maximum entropy : the interface between physics, biology, economics and information theory /

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.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Fort, Hugo (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2022]
Colección:IOP (Series). Release 22.
IOP ebooks. 2022 collection.
Temas:
Maximum entropy method.
Information theory > Forecasting.
Information theory.
MATHEMATICS / Probability & Statistics / General.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 1. Entropy as missing information : from Shannon's information theory to Jaynes' maximum entropy principle
  • 1.1. Information and its processing in biology, economics and physics
  • 1.2. Uncertainty in communication systems : Shannon entropy
  • 1.3. Entropy as missing information
  • 1.4. Working with incomplete information : the principle of maximum entropy to find minimally prejudiced distributions
  • 2. The synthesis of information theory and thermodynamics : Shannon entropy and Boltzmann entropy are the same thing
  • 2.1. Basics of statistical physics
  • 2.2. MaxEnt derivation of statistical mechanics
  • 2.3. Converting information into energy : from Maxwell's demon to Landauer's eraser
  • 2.4. Conclusion
  • 3. Elements of physical biology : the Lotka-Volterra equations
  • 3.1. The kinetic formulation of population dynamics
  • 3.2. The Lotka-Volterra linear model for single-trophic communities
  • 3.3. The statistical mechanics of populations
  • 3.4. Conclusion
  • Appendix A. Equilibrium stability in population ecology
  • 4. Economics as physics, economics as biology
  • 4.1. Economics as social physics, physics as Nature's economics
  • 4.2. Neoclassical economics
  • 4.3. Economics as biology, or evolutionary economics
  • 4.4. Selection dynamics
  • 4.5. Linking selection dynamics with ecology and physics
  • 4.6. Innovation through mutations
  • 4.7. Implementing evolution in economics
  • 4.8. The 'Marshall problem' or a transdisciplinary synthetic perspective of economics
  • 5. Inferring effective interaction matrices through MaxEnt
  • 5.1. Working with imperfect information
  • 5.2. The Lotka-Volterra maximum entropy interaction matrix
  • 5.3. How good is the pairwise approximation?
  • 6. Early warning indications of species crashes from effective intraspecific interactions in tropical forests
  • 6.1. Background : diversity loss and early warning signals
  • 6.2. Goal
  • 6.3. Data
  • 6.4. Estimating the interaction matrix through MaxEnt
  • 6.5. Intraspecific competition interactions are enough to predict the trajectories of tree species
  • 6.6. A new early warning signal
  • 6.7. Conclusion, caveats and future developments
  • 7. Modelling markets as ecosystems with the help of maximum entropy
  • 7.1. Background : a short history of market modelling
  • 7.2. Goal
  • 7.3. Data
  • 7.4. Modelling : replicator dynamics combined with pairwise maximum entropy or RDPME model
  • 7.5. Model validation
  • 7.6. Conclusion : balance, caveats, extensions and improvements
  • Appendix A. A metric to measure the pace of change of the payoff matrix
  • 8. Glossary.

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