Predictive Inference: An Introduction: 55 (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) - Hardcover

Geisser, Seymour

Hardcover

ISBN 10: 0412034719 ISBN 13: 9780412034718

Publisher: Springer, 1993

Synopsis

The author's research has been directed towards inference involving observables rather than parameters. In this book, he brings together his views on predictive or observable inference and its advantages over parametric inference. While the book discusses a variety of approaches to prediction including those based on parametric, nonparametric, and nonstochastic statistical models, it is devoted mainly to predictive applications of the Bayesian approach. It not only substitutes predictive analyses for parametric analyses, but it also presents predictive analyses that have no real parametric analogues. It demonstrates that predictive inference can be a critical component of even strict parametric inference when dealing with interim analyses. This approach to predictive inference will be of interest to statisticians, psychologists, econometricians, and sociologists.

About this title

Review

..."this monograph is a very welcome attempt to shift back the main emphasis of statistics from parametric estimation and testing to prediction which, as noted by the author, was originally the earliest and most prealent form of statistical inference...I am sure all statisticians and students of statistics with an open mind will enjoy reading it and, hopefully will appreciate the beauty and usefulness of a coherent predictive view of their subject." -Mathematical Reviews "Predictive Inference: An Introduction is rich both in the coverage of topics and in applications...The monograph is addressed to statisticians and research workers who are intrested in the predictive approach. Its major contribution is likely to be as a resource for persons interested in trying predictive inference in some application." -Journal of the ASA

Synopsis

The author's research has been directed towards inference involving observables rather than parameters and in this book he brings together his views on predictive or observable inference and his reason for his preference. He feels that inference couched in terms of observables has the possibility of being validated. While the book discusses a variety of approaches to prediction including those based on parametric, nonparametric, and non-stochastic statistical models, it is devoted mainly to predictive applications of the Bayesian approach. It not only substitutes predictive analyses for parametric analyses, but also presents predictive analyses that have no real parametric analogues. It also demonstrates that predictive inference can be a critical component of even strict parametric inference when dealing with interim analyses. This book should be of interest to undergraduates and graduates in statistics, economy, psychology, sociology.

Edition details

• Publisher: Springer
• Publication date: 1993
• ISBN 10: 0412034719
• ISBN 13: 9780412034718
• Binding: Hardcover
• Language: English
• Edition number: 1
• Number of pages: 280