Optimal design

An approach to experimental design in which the allocation of experimental runs is chosen to optimize a mathematical criterion based on the Fisher information matrix. Common criteria include D-optimality (minimizing parameter estimate variance), A-optimality, and G-optimality. Useful when classical factorial designs are infeasible.