
Bayesian Probability Theory
Applications in the Physical Sciences
- 654 pages
- English
- PDF
- Available on iOS & Android
Bayesian Probability Theory
Applications in the Physical Sciences
About this book
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.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright
- Contents
- Preface
- PART I Introduction
- PART II Assigning probabilities
- PART III Parameter estimation
- PART IV Testing hypotheses
- PART V Real-world applications
- PART VI Probabilistic Numerical Techniques
- Appendix A Mathematical compendium
- Appendix B Selected proofs and derivations
- Appendix C Symbols and notation
- References
- Index
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