Covering all aspects of probability theory, statistics and data analysis from a Bayesian perspective, this book is ideal for graduate students and researchers. It presents the roots, applications and numerical implementation of probability theory, covers advanced topics and features real-world problems.
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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