A0420
Title: Uniform designs of experiments with mixtures under the criterion mean L1-distance
Authors: Yaping Wang - East China Normal University (China) [presenting]
Abstract: Mixture experiments analyze how changes in component proportions impact the response variable within the experimental region of a simplex. A new criterion, named the mean L1-distance (ML1D) criterion is introduced, for constructing uniform designs in mixture experiments. This criterion allows flexibility in point size and showcases a more uniform pattern within the experimental region. The optimal Scheffe-type simplex-lattice designs are also explored under the ML1D criterion. An interesting discovery is that the uniform mixture designs and the optimal Scheffe-type simplex-lattice designs are connected. For a two-component mixture design, these two types of designs are proven to be equivalent. For more than two-component mixture designs, numerical equivalences between the two designs are observed. These findings strengthen the rationale for users to adopt these designs in mixture experiments for modeling and prediction.
