Mixture Experiments : All-Variance and Minimum-Bias Designs

Abstract

The problem considered is that of finding designs in case of inadequacy in the model of a mixture experiment. Box and Draper (1959) proposed for comparing designs, the Integrated Mean Square Error (IMSE) criterion which is composed of integrated variance and integrated bias. A class of augmented axial designs $Δ_{q} = {Δ (δ_{1}, δ_{2}; a, β, q); 0 ⩽ δ_{1} ⩽ \frac{q - 1}{q}, 0 ⩽ δ_{2} ⩽ \frac{1}{q}; 0 ⩽ a, β; a + β ⩽ 1}$ is proposed and is used to find the all-variance and all-bias designs for the first and second degree model.

Keywords

Mixture experiments axial design integrated mean square error all-variance design all-bias design

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