From the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions, stochastic processes, parameter estimation, model selection, hypothesis testing and experimental design. In addition, it explores state-of-the art numerical techniques required to solve demanding real-world problems. The book is ideal for students and researchers in physical sciences and engineering.

About the Authors

Wolfgang von der Linden is Professor for Theoretical and Computational Physics at the Graz University of Technology. His research area is statistical physics with focus on strongly correlated quantum-many-body physics, based on computational techniques.

Volker Dose is a former Director of the surface physics division of the Max Planck Institute for plasma physics. He has contributed to Bayesian methods in physics, astronomy and climate research.

Udo von Toussaint is a Senior Scientist in the material research division of the Max Planck Institute for plasma physics, where he works on Bayesian experimental design, data fusion, molecular dynamics and inverse problems in the field of plasma-wall interactions.

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Bayesian Probability Theory: Applications in the Physical Sciences

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