Provides an accessible foundation to Bayesian analysis using
real world models
This book aims to present an introduction to Bayesian modelling
and computation, by considering real case studies drawn from
diverse fields spanning ecology, health, genetics and finance. Each
chapter comprises a description of the problem, the corresponding
model, the computational method, results and inferences as well as
the issues that arise in the implementation of these
approaches.
Case Studies in Bayesian Statistical Modelling and
Analysis:
* Illustrates how to do Bayesian analysis in a clear and concise
manner using real-world problems.
* Each chapter focuses on a real-world problem and describes the
way in which the problem may be analysed using Bayesian
methods.
* Features approaches that can be used in a wide area of
application, such as, health, the environment, genetics,
information science, medicine, biology, industry and remote
sensing.
Case Studies in Bayesian Statistical Modelling and
Analysis is aimed at statisticians, researchers and
practitioners who have some expertise in statistical modelling and
analysis, and some understanding of the basics of Bayesian
statistics, but little experience in its application. Graduate
students of statistics and biostatistics will also find this book
beneficial.
About the author
Clair Alston, Queensland University of Technology and Science, Australia.
Kerrie L. Mengersen, Queensland University of Technology and Science, Australia.
Tony Pettitt, Queensland University of Technology and Science, Australia.
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