276 Pages
by
Chapman & Hall
276 Pages
by
Chapman & Hall
240 Pages
by
Chapman & Hall
Also available as eBook on:
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... Read more
1. Introduction 2. Non-Bayesian Predictive Approaches 3. Bayesian prediction 4. Selecting a Statistical Model and Predicting 5. Problems of comparison and allocation 6. Perturbation Analysis 7. Process control and optimization 8. Screening tests for detecting a characteristic 9. Multivariate normal prediction 10. Interim analysis and sampling curtailment
Biography
Geisser, Seymour
