A Note on Model Selection in Mixture Experiments

Abstract

In mixture experiments, determination of the best model for modeling the mixture system is significant in both understanding and interpreting the system. For obtaining the best model in mixture experiments, different methods have been used. Most commonly used methods are the stepwise type methods. However, the models obtained with these methods are not always the best model depending on the chosen criteria. As the models obtained with these methods can be affected by collinearity, in this paper, an alternative approach is used for the determination of the models taken into account in the modeling of the mixture surface, which is obtained on the experimental region. This approach depends on the examination of all possible subset regression models obtained for the mixture model. To determine the best subset model, the condition numbers of models and the model control graphs are also taken into account. Then, proposed approach has been investigated on flare data set, which is widely known in literature.