Bayesian Inference
About this book
The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers.
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Table of contents
- Bayesian Inference
- Contents
- Preface
- Section 1 Theoretical Foundations of Bayesian Inference
- Section 2 Applications of Bayesian Inference in Life Sciences
- Section 3 Applications of Bayesian Inference in Engineering
- Section 4 Applications of Bayesian Inference in Economics
