A candidate‐set‐free algorithm for generating D‐optimal split‐plot designs

Bradley Jones and Peter Goos ()

Journal of the Royal Statistical Society Series C, 2007, vol. 56, issue 3, 347-364

Abstract: Summary. We introduce a new method for generating optimal split‐plot designs. These designs are optimal in the sense that they are efficient for estimating the fixed effects of the statistical model that is appropriate given the split‐plot design structure. One advantage of the method is that it does not require the prior specification of a candidate set. This makes the production of split‐plot designs computationally feasible in situations where the candidate set is too large to be tractable. The method allows for flexible choice of the sample size and supports inclusion of both continuous and categorical factors. The model can be any linear regression model and may include arbitrary polynomial terms in the continuous factors and interaction terms of any order. We demonstrate the usefulness of this flexibility with a 100‐run polypropylene experiment involving 11 factors where we found a design that is substantially more efficient than designs that are produced by using other approaches.

Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9876.2007.00581.x

Related works:
Working Paper: A candidate-set-free algorithm for generating D-optimal split-plot designs
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:bla:jorssc:v:56:y:2007:i:3:p:347-364

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().