Predictive Inference

Seymour Geisser, D.R. Cox (Nuffield College, Oxford University, UK), N. Reid (University of Toronto, Ontario, Canada) , Valerie Isham

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English

Chapman & Hall/CRC
03 December 2019

Psychological theory & schools of thought; Psychological methodology; Probability & statistics

Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability

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.

By: Seymour Geisser
Series edited by: D.R. Cox (Nuffield College Oxford University UK), N. Reid (University of Toronto, Ontario, Canada), Valerie Isham, R.J. Tibshirani (Stanford university Stanford University Stanford University, California, USA Stanford University, California, USA)
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 216mm, Width: 138mm,
Weight: 335g
ISBN: 9780367449919
ISBN 10: 0367449919
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Pages: 276
Publication Date: 03 December 2019
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Geisser, Seymour

Reviews for Predictive Inference

...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