Optimal Design is depends on the statistical model and is assessed with respect to a statistical criterion, which is related to the variance-matrix of the estimator. It is a group of the “best” design points selected when reducing or augmenting the number of experimental runs in the original design. It allow parameters to be estimated without bias and with minimum variance. It can accommodate multiple types of factors, such as process, mixture, and discrete factors. It can also be optimized when the design-space is constrained, for example, when the mathematical process-space contains factor-settings that are practically infeasible.
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