Kendall's Advanced Theory Statistics: Bayesian Inference (Volume 2B)

O'hagan, Anthony

ISBN 10: 0340529229 / ISBN 13: 9780340529225

Edité par Hodder Education, 1994

A propos de cet article

Volume 2b. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,950grams, ISBN:0340529229.

N° de réf. du vendeur 4143535

Détails bibliographiques

• Titre: Kendall's Advanced Theory Statistics: Bayesian Inference (Volume 2B)
• Éditeur: Hodder Education
• Date de parution: 1994
• Langue: anglais
• ISBN à 10 chiffres: 0340529229
• ISBN à 13 chiffres: 9780340529225
• Reliure: Couverture rigide
• État de l'article: Good
• Catalogues du vendeur:
  • Mathematics

A propos de ce titre

Synopsis

This volume deals with the fundamental theory and principles of Bayesian inference, including estimation, hypothesis testing, and the linear model. The coverage provided overlaps with that of "Kendall's Advanced Theory of Statistics, Volumes 1 and 2" from a Bayesian viewpoint, and cross-referencing is provided where appropriate. Thinking common to both Classical and Bayesian theory is not repeated. A major source and reference, covering advanced level theory at a level which every professional statistician needs to know before specializing, the book also provides an introduction to other major fields which are covered in other books in this series. This book should be of interest to professional statisticians and statistical libraries.

Présentation de l'éditeur

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.