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Keywords:

Science & Technology, Technology, Physical Sciences, Computer Science, Interdisciplinary Applications, Statistics & Probability, Computer Science, Mathematics, AVERAGE EFFICIENCY FACTOR, RESPONSE-SURFACE DESIGNS, CONSTRUCTION, ALGORITHM, 0104 Statistics, 0802 Computation Theory and Mathematics, 1403 Econometrics, 3802 Econometrics, 4905 Statistics

Abstract:

For the algorithmic construction of optimal experimental designs, it is important to be able to evaluate small modifications of given designs in terms of the optimality criteria at a low computational cost. This can be achieved by using powerful update formulas for the optimality criteria during the design construction. The derivation of such update formulas for evaluating the impact of changes to the levels of easy-to-change factors and hard-tochange factors in split-plot designs as well as the impact of a swap of points between blocks or whole plots in block designs or split-plot designs is described. © 2009 Elsevier B.V. All rights reserved.