Update formulas for split-plot and block designs

Heidi Arnouts and Peter Goos ()

Computational Statistics & Data Analysis, 2010, vol. 54, issue 12, 3381-3391

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.

Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-9473(09)00425-3
Full text for ScienceDirect subscribers only.

Related works:
Working Paper: Update formulas for split-plot and block designs (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:54:y:2010:i:12:p:3381-3391

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().