Bayesian D-Optimal and Model Robust Designs in Linear Regression Models

DOI10.1080/02331889308802429zbMath0816.62054OpenAlexW2027102258MaRDI QIDQ4763443

Dette, Holger

Publication date: 10 April 1995

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331889308802429

zbMATH Keywords

prior distributionnested modelsBayesian optimal designD-optimal designElfving's theorem\(c\)-optimalitymodel robust designsprecision matricesexpected posterior risks

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Optimal statistical designs (62K05)

Related Items (10)

Admissible minimum bias estimation of response surfaces ⋮ Optimal design for prediction in multiresponse linear models based on rectangular confidence region ⋮ On proportional volume sampling for experimental design in general spaces ⋮ Optimal designs which are efficient for lack of fit tests ⋮ A new characterization of Elfving's method for high dimensional computation ⋮ Geometric characterization of \(D\)-optimal designs for random coefficient regression models ⋮ D-optimal minimax regression designs on discrete design space ⋮ Bayesian sequential \(\mathscr D\)-\(\mathscr D\) optimal model-robust designs ⋮ Model-robust and model-sensitive designs ⋮ Minimax designs for linear regression models with bias in a reproducing kernel Hilbert space in a discrete set

Cites Work

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• Optimal Bayesian experimental design for linear models
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• Robust Bayesian experimental designs in normal linear models
• Bayesian optimal designs for linear regression models
• General equivalence theory for optimum designs (approximate theory)
• The Equivalence of Two Extremum Problems
• Optimum Designs in Regression Problems, II
• A note on Bayes designs for inference using a hierarchical linear model
• Experimental design in a class of models
• Optimal multipurpose designs for regression models
• Optimal Experimental Designs
• Optimum Allocation in Linear Regression Theory
• Robust Statistics

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