Overview
- Introduces a new theory of probabilistic risk analysis that is rigorous and versatile
- Explains how risk analysis is related to Bayesian decision theory
- Provides many examples, all with R-code
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
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Table of contents (19 chapters)
Keywords
About this book
Authors and Affiliations
About the authors
Mark Brewer is director of BioSS (Biomathematics and Statistics Scotland). His first degree was in Probability and Statistics from the University of Sheffield, and Mark subsequently studied for a PhD in statistics - specialising in MCMC and graphical models - at the University of Edinburgh. After three years working in statistical consultancy at the University of Aberdeen and five years as a lecturer in statistics at the University of Exeter, in 2001 Mark moved to BioSS as a senior statistician. He has worked mainly in ecological and environmental applications, conducting research in spatio-temporal and Bayesian modelling. He became head of BioSS in 2018, and has seen the organisation increase both its funding and staffing complement since that time. Mark acted as co-Editor for Biometrics (2019-2021) and was previously on the Executive Board of the International Biometric Society (2017-2020).
Bibliographic Information
Book Title: Probabilistic Risk Analysis and Bayesian Decision Theory
Authors: Marcel van Oijen, Mark Brewer
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-3-031-16333-3
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Softcover ISBN: 978-3-031-16332-6Published: 24 November 2022
eBook ISBN: 978-3-031-16333-3Published: 23 November 2022
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: XIII, 114
Number of Illustrations: 1 b/w illustrations
Topics: Statistical Theory and Methods, Biostatistics, Bayesian Inference