Bayesian estimation and experimental design in linear regression models
著者
書誌事項
Bayesian estimation and experimental design in linear regression models
（Wiley series in probability and mathematical statistics）
J. Wiley, 1988
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注記
Bibliography: p. [275]-290
内容説明・目次
内容説明
This research monograph is concerned with the design and analysis of linear regression experiments, using the Bayesian approach. The construction methods and design algorithms developed in the book will be of direct practical use to all those involved in the design and analysis of regression experiments, and are designed to be adapted for use in computer programs.
目次
- Estimation and Design as a Bayesian Decision Problem
- Choice of a Prior Distribution
- Conjugate Prior Distributions
- Bayes Estimation of the Regression Parameter
- Optimality and Robustness of the Bayes Estimator
- Bayesian Interpretation of Estimators Using Non-Bayesian Prior Knowledge
- Bayes Estimation in Case of Prior Ignorance
- Further Problems
- The Design Problem for the Linear Bayes Estimator
- Characterization of Optimal Designs
- Construction of Optimal Continuous Designs
- Construction of Exact Optimal Designs.
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