Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415999 | Computational Statistics & Data Analysis | 2010 | 11 Pages |
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-to-change 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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Heidi Arnouts, Peter Goos,