Bayesian Methods
Bayesian Methods
AUD$83.59
exc GSTThis book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. It is unusual in presenting Bayesian statistics with a practical flavor and an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data. The authors draw on many years of experience with practical and research programs and describe many statistical methods, not readily available elsewhere. A first chapter on Fisherian methods, together with a strong overall emphasis on likelihood, makes the text suitable for mainstream statistics courses whose instructors wish to follow mixed or comparative philosophies. The other chapters contain important sections relating to many areas of statistics such as the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practical examples, worked examples, and exercises. It will be essential reading for all statisticians, statistics students, and related interdisciplinary researchers.
- Numerous worked examples, self-study exercises, and practical applications
- Many statistical methods
- Bayesian statistics with a practical flavor; directed towards mainstream statistics, and how to infer scientific, medical, and social conclusions from your numerical data
Reviews & endorsements
'… challenging and worthwhile … this book is a very welcome and original contribution to the literature on Bayesian statistics.' J. V. Zidek, ISI Short Book Reviews
'The book makes interesting reading and the breadth of ideas tackled by the authors is enormous … deserves a place in the university library as well as in the personal libraries of researchers who are interested in the Bayesian approach.' Carmen Fernández, The Statistician
'The book is highly recommended as a well written intermediate book on some modern topics of Bayesian analysis.' H. K. van Dijk, Niew Archief voor Wiskunde
'The explanations stated in the book are very clear, the detailed computations, and the particular way of describing problems, theorems and applications in this book make it useful into only for statisticians but also for other researchers who are confronted with problems of data analysis and who are not primarily familiar with statistical methods.' Monatshefte für Mathematik
'A very readable and interesting book.' Indian Journal of Statistics
Product details
November 2001Paperback
9780521004145
348 pages
253 × 180 × 19 mm
0.74kg
69 b/w illus. 27 tables 150 exercises
Available
Table of Contents
- 1. Introductory statistical concepts
- 2. The discrete version of Bayes' theorem
- 3. Models with a single unknown parameter
- 4. The expected utility hypothesis and its alternatives
- 5. Models with several unknown parameters
- 6. Prior structures, posterior smoothing, and Bayes-Stein estimation
- Guide to worked examples
- Guide to self-study exercises.
