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Inhaltsangabe
Kendall's objective in setting out to write the original Kendall's Advanced Theory of Statistics, published in two volumes in 1943 and 1946, was 'to develop a systematic treatment of [statistical theory] as it exists at the present time.' With this aim in mind, the first edition of Bayesian Inference was added as Volume 2B of the Kendall's Advanced Theory of Statistics in 1994, to introduce the new and rapidly growing field of Bayesian statistics. This new edition is a response to the developments and advances that have taken place in this area over the last few years and offers the reader an up-to-date and comprehensive overview of Bayesian statistics. The second edition of Bayesian Inference has been expanded to include new chapters on Markov Chain Monte Carlo methods, discrete data models and non-parametric models. Existing chapters have also been thoroughly revised and updated and there is greater coverage of computational methods and of model comparison and criticism. There is also a new chapter of case studies, providing practical illustrations of the theory presented throughout the book.Like the other volumes in the Kendall's Library of Statistics, the first edition of Bayesian Inference provided a good selection of exercises at the end of each chapter. This popular feature is retained in the new edition, with many new exercises to deepen the reader's understanding. Clearly written and offering a wide-ranging introduction to Bayesian statistics, this book will be an essential reference source for students, researchers and practitioners in statistics.
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Über die Autorin bzw. den Autor
Anthony O'Hagan is Professor of Statistics at the University of Sheffield, UK Jon Forster is Reader in Statistics at the University of Southampton, UK
Von der hinteren Coverseite
It is now generally recognised in many areas of the social, medical and other sciences that statistical data typically have complex hierarchical or multilevel structures in which individuals are grouped together in communities or institutions. This grouping affects their behaviour and multilevel modelling is now the accepted statistical technique for the analysis of this type of data. An understanding of these methods is vital for researchers in fields such as education, epidemiology, geography, child growth and social surveys, among others. This new edition brings the book fully up to date, explaining important new developments such as the use of Markov Chain Monte Carlo methods, bootstrapping and mulitvariate models. The book has been completely restructured for this third edition and extra space has been given to discussion of key issues such as missing data, measurement errors and multivariate models. Real-life examples are used throughout to illustrate clearly the theoretical concepts.
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- VerlagHodder Arnold
- Erscheinungsdatum2004
- ISBN 10 0340807520
- ISBN 13 9780340807521
- EinbandTapa dura
- SpracheEnglisch
- Auflage2
- Anzahl der Seiten480
- Kontakt zum HerstellerNicht verfügbar
(Keine Angebote verfügbar)
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