Predictive Inference

Front Cover
CRC Press, Jun 1, 1993 - Mathematics - 240 pages
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.

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Bayesian prediction
Problems of comparison and allocation
Perturbation analysis
Screening tests for detecting a characteristic
Multivariate normal prediction
Interim analysis and sampling curtailment
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Page 257 - R. (1986). Evaluation of a confidential method of excluding blood donors exposed to human immunodeficiency virus. Transfusion 26, 539-541.
Page 258 - San Martini, A. and Spezzaferri, F. (1984) A predictive model selection criterion.

About the author (1993)

Geisser\, Seymour