Bayesian estimation and experimental design in linear regression models

書誌事項

Bayesian estimation and experimental design in linear regression models

Jürgen Pilz

(Wiley series in probability and mathematical statistics)

J. Wiley, 1991

[Licensed ed.]

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注記

Bibliography: p. [275]-290

Includes index

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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