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5. Process Improvement
5.5. Advanced topics
5.5.4. What is a mixture design?

5.5.4.3.

Simplex-centroid designs

Definition of simplex-
centroid designs
A second type of mixture design is the simplex-centroid design. In the q-component simplex-centroid design, the number of distinct points is 2q - 1. These points correspond to q permutations of (1, 0, 0, ..., 0) or q single component blends, the (q choose 2) permutations of (.5, .5, 0, ..., 0) or all binary mixtures, the (q choose 3) permutations of (1/3, 1/3, 1/3, 0, ..., 0), ..., and so on, with finally the overall centroid point (1/q, 1/q, ..., 1/q) or q-nary mixture.
The design points in the Simplex-Centroid design will support the polynomial
Model supported by simplex-
centroid designs
E(Y) = SUM[i=1 to q][beta(i)*x(i) +
 SUM[j=1 to q][SUM[i < j][beta(ij)*x(i)*x(j) +
 SUM[k=1 to q][SUM[j < k][SUM[i < j][beta(ijk)*x(i)*x(j)*x(k) + ... +
 beta(12...q)*x(i)*x(j)*...*x(q)]]]

which is the qth-order mixture polynomial. For q = 2, this is the quadratic model. For q = 3, this is the special cubic model.

Example of runs for three and four components For example, the fifteen runs for a four component (q = 4) simplex-centroid design are:
    (1,0,0,0), (0,1,0,0), (0,0,1,0), (0,0,0,1), (.5,.5,0,0), (.5,0,.5,0) ..., (0,0,.5,.5), (1/3,1/3,1/3,0), ...,(0,1/3,1/3,1/3), (1/4,1/4,1/4,1/4).
The runs for a three component simplex-centroid design of degree 2 are
    (1,0,0), (0,1,0), (0,0,1), (.5,.5,0), (.5,0,.5), (0,.5,.5), (1/3, 1/3, 1/3).
However, in order to fit a first-order model with q =4, only the five runs with a "1" and all "1/4's" would be needed. To fit a second-order model, add the six runs with a ".5" (this also fits a saturated third-order model, with no degrees of freedom left for error).
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