Abstract
We will be considering what Lindley (1968) in his paper on the choice of variables in multiple regression termed 'a prediction problem'. By this we mean that data from a regression experiment is analyzed in such a way that we can predict a future value of the dependent variable and choose which independent variables to use for the prediction. In this paper, the regression experiment is designed, i.e. the levels of the independent variables are selected. Our object is to find the optimal design. Although many papers have been published on obtaining optimal regression designs, the approach of this paper is different in that it uses Bayesian decision theory rather than orthodox (classical) methods. Lindley (1968) considered the prediction problem given the results of the regression experiment, and we shall be using some of his results in this paper.
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