Scheffé Mix Models
Scheffé models were specifically developed to handle the natural constraints of
mixture designs.
Mixture models are only readily interpretable when the mixture components all go
from 0 to the total for the design. Most mixture designs cover a more
constrained space. Use the Model Graphs to better understand the models.
The Scheffé model forms are as follows:
Linear
\[\hat{y}= \sum_{i=1}^{q}\beta _{i} x_{i}\]
Example
\[12A + 8B + 4C\]
Quadratic
\[\hat{y}=\sum_{i=1}^{q}
\beta_{i}x_{i}\,+\sum_{i<j}^{q-1}\sum_{j}^{q} \beta_{ij} x_{i} x_{j}\]
Example
\[12A + 8B +4C + 8AB - 8AC\]
Special Cubic
\[\hat{y} \sum_{i=1}^{q}
\beta_{i}x_{i}+\sum_{i<j}^{q-1}\sum_{j}^{q}
\beta_{ij}x_{i}x_{j}+\sum_{i<j}^{q-2}\sum_{j<k}^{q-1}\sum_{k}^{q}\beta_{ijk}
x_{i}x_{j}x_{k}\]
Example
\[12A + 8B + 4C + 8AC - 8BC + 54ABC\]
Full Cubic
\[\hat{y}=\sum_{i=1}^{q}\beta_{i}x_{i}+\sum_{i<j}^{q-1}
\sum_{j}^{q}\beta_{ij}x_{i}x_{j}+\sum_{i<j}^{q-1}\sum_{j}^{q}\delta_{ij}x_{i}
x_{j}(x_{i}-x_{j})+\sum_{i<j}^{q-2}\sum_{j<k}^{q-1}\sum_{k}^{q}\beta_{ijk}x_{i}
x_{j}x_{k}\]
Example
\[12A + 8B + 4C + 8AB - 8AC + 54ABC + 48AC(A - C)\]
Standard Scheffé polynomials are available up to the fourth order. There are
also partial quadratic mixture (PQM) models using a combination of linear,
squared, and quadratic terms.
References
G. Piepel, J. Szychowski, and J. Loeppky. Augmenting scheffe linear mixture models with squared and/or crossproduct terms. Journal of Quality Technology, 2002.