Bayesian Estimating and Experimental Design in Linear Regression Models

BAYESIAN REGRESSION AND PRIOR DISTRIBUTIONS. Estimation and Design as a Bayesian Decision Problem. Choice of a Prior Distribution. Conjugate Prior Distributions. BAYESIAN ESTIMATION. Bayes Estimation of the Regression Parameter. Optimality and Robustness of the Linear Bayes Estimator. Characterization of Bayes and Admissible Linear Estimators. Bayes Estimation in Case of Prior Ignorance. Further Problems. BAYESIAN EXPERIMENTAL DESIGN. The Design Problem for the Linear Bayes Estimator. Characterization of Optimal Designs. Construction of Optimal Continuous Designs. Construction of Exact Optimal Designs. Further Problems. MINIMAX AND ADMISSIBLE LINEAR REGRESSION ESTIMATION WITH RESTRICTED PARAMETER REGIONS. Minimax Linear and Affine Estimation in True Models. Admissible Linear Estimation Under Parameter Restrictions. The Minimax Approach to Fitting Biased Response Surfaces. Appendix. References. Glossary. Subject Index.Pilz, Jurgen is the author of 'Bayesian Estimating and Experimental Design in Linear Regression Models', published 1989 under ISBN 9780471917328 and ISBN 047191732X.