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Bayesian analysis of linear models. (English) Zbl 0564.62020
Statistics: Textbooks and Monographs, Vol. 60. New York - Basel: Marcel Dekker, Inc. XII, 454 p. $ 59.75 (U.S. & Canada); $ 71.50; SFr. 179.00 (all other countries) (1985).
This book is intended for a graduate course. It is very much in the spirit of G. E. P. Box and G. C. Tiao, Bayesian inference in statistical analysis. (1973; Zbl 0271.62044), in giving scant attention to the loss function, being mainly concerned with finding the posterior distribution and its characteristics, such as moments. This reviewer is uncomfortable with efforts at Bayesian analysis without loss functions. Chapter titles give a good idea of the contents.
1. Bayesian inference for the general linear model. (Includes introduction to Bayesian analysis). 2. Linear statistical models and Bayesian inference. 3. The traditional linear models. 4. The mixed model.
5. Time series models. 6. Linear dynamic systems. 7. Structural change in linear models. 8. Multivariate linear models. 9. Looking ahead.
Reviewer: M.Fox

62F15 Bayesian inference
62J10 Analysis of variance and covariance (ANOVA)
62-02 Research exposition (monographs, survey articles) pertaining to statistics
62F03 Parametric hypothesis testing
62F10 Point estimation
62M20 Inference from stochastic processes and prediction
62J05 Linear regression; mixed models
62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)