Abstract

CRUZ-SALGADO, Javier. Comparing the Intercept Mixture Model with the Slack-Variable Mixture Model. Ing. invest. y tecnol. [online]. 2016, vol.17, n.3, pp.383-393. ISSN 2594-0732.

Mixture experiments are experiments performed using ingredients whose proportions are restricted. This restriction may result in extremely small range in terms of the mixtures, causing difficulties in model fitting arising from ill-conditioning. The choice of model form is a very important factor in the numerical stability of the information matrix. In this paper, the intercept model is compared against the slack-variable model for mixture experiments. We analyzed if it matter which component is replaced for the constant term in the intercept model, in the sense on numerical stability. We also show by numerical examples that the Correlation Criterion, presented in Kang et al. (2015), does not work for the intercept model. Next, as suggested in the literature, we use linear transformation to alleviate the numerical instability. In addition, we try four transformation methods and choose the best one for the intercept model and the slack-variable model. Finally, we compare the intercept model with the slack-variable model based mainly on the prediction accuracy and numerical stability.

Keywords : mixture experiments; intercept model; slack-variable model; variable transformation; condition number; variance inflation factor.

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