Optimal designs for minimax-criteria in random coefficient regression models
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We consider minimax-optimal designs for the prediction of individual parameters in random coefficient regression models. We focus on the minimax-criterion, which minimizes the “worst case” for the basic criterion with respect to the covariance matrix of random effects. We discuss particular models: linear and quadratic regression, in detail.
KeywordsRandom coefficient regression Optimal designs Prediction Integrated mean squarer error Minimax-criterion
The author is grateful to two anonymous referees and the guest editor for helpful comments which improved the presentation of the results.
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